bluuebunny/crossref_metadata_2025 huggingface dataset:
On Reserve Money for a Fuzzy EOQ Model in an Inflationary Environment Under Supplier Credit
Authors: Duari Nirmal Kumar , Chakrabarti Tripti
Published: February 2018

We propose to derive a deterministic inventory model for a time varying deterioration rate with an exponential fuzzy demand over a finite planning horizon in this study. We assume that the supplier offers a credit limit to the retailer during which there is no interest charged. However, the retailer has the reserve capital with him to make the payments at the beginning of the transaction, but he decides to take the benefit of the credit limit. Each cycle has shortages, which have been partially backlogged to suit present day competition in the market. Also, the whole study has been done in an inflationary environment using the Discounted Cash Flow (DCF) approach to impart economic feasibility to the model. Numerical examples have been presented with the help of lingo software.
Optimal Control of the Integrated Marketing-Production Planning Problem
Authors: Reid Jill , Tadj Lotfi
Published: February 2018

We consider in this paper the integrated marketing – production planning problem and propose an optimal control approach to derive the optimal solution. The state variables are the inventory level and the stock of goodwill and the control variables are the production rate and the advertising rate. Both cases where the firm adopts a continuous-review and a periodic-review policy are considered. The optimal states and controls are obtained explicitly. Illustrative examples are presented. Sensitivity analysis shows the effect of some system parameters on the optimal solution.
Modeling Adoption of a Successive Generational Product in Multiple Markets
Authors: Anand Adarsh , Bansal Gunjan , Agarwal Mohini
Published: February 2018

Companies that have been following the innovation mantra have also understood the importance of coming up with successive generations for their offerings. Continuous enhancement of existing technologies or emergence of new technologies has made this improvement possible. In today's neck to neck competitive environment firms introduce their products in more than one market so as to widen their spectrum of visibility and availability. This has allowed customers to avail the facility from more than one place (segment) simultaneously. In the present proposal, we have come up with a mathematical framework to capture the impact of multi-generations on multiple markets and vice-versa. Further, consideration of cross-generation shifting makes our analysis more comprehensive.
Spare Parts Inventory Management Literature and Direction Towards the Use of Data Mining Technique
Authors: Sarmah S. P. , Moharana Umesh Chandra
Published: February 2018

In the current age of information technology, most of the industries have implemented integrated information systems or enterprise resource planning applications to automate their business process, reduce lead time, improve productivity and reduce cost. These industries generate large amount of inventory and maintenance related data on daily basis, which are stored in a central database. Data mining techniques are most suitable to discover valuable information from this large amount of data. The valuable information can be in the form of patterns, associations, classifications, changes etc. which can be helpful for maintenance and inventory managers for better decision making. This chapter reviews application of data mining technique in inventory management through a survey of literature and classified the articles. Also the chapter suggests other inventory management areas where data mining techniques can be applied for better decision making. Keywords and abstracts were used to identify 107 articles concerning management of inventory and application of data mining techniques.
A Comparative Analysis of Africa and Chinese Crowdfunding Markets
Authors: Chirisa Innocent , Mukarwi Liaison
Published: February 2018

This chapter compares the African and Chinese crowdfunding markets with a view to draw lessons from the two markets. China has a longer experience than Africa in the crowdfunding activities; crowdfunding processes in the country may not be directly applicable to the African states, but there are lessons that can be learnt by individual or group of African or Asian governments. These differing experiences identified can serve as a practical guide for urban development actors longing for sustainable funding for important urban development projects. In order to gather this data, the authors conducted a desktop review of literature, both grey and published being work on crowdfunding in Africa and China. Data collected were analysed using thematic content analysis. The chapter argues that the low adoption of crowdfunding by Africa can be attributed to a number of factors, including national regulatory environments that are not conducive for crowdfunding of equity and debt, and unconducive technological environments where e-commerce is not widely utilised.
Crowdsourcing as a Tool for Improving Learning in Tertiary Institutions in Developing Countries
Authors: Benna Indo
Published: February 2018

Higher education in many developing countries faces the triple challenges of inadequate funding, need to improve quality of learning outcomes, and the pressure to increase quality of graduates. Crowdsourcing offers opportunity for institutions to face these problems with little resource expenditure. The chapter describes/analyzes how crowdsourcing can be applied in curriculum and teaching material development activities through collaborative efforts of higher education institutions from different parts of the world to develop suitable curriculum for teaching English for specific purpose. The chapter analyzes the process and the evaluates the outcome of the crowdsourcing tool and suggests that its application can keep higher education institutions in developing countries in forefront of education and research innovation, and prepares members in these institutions for innovative problem solving and for the challenges of the online world.
Mentoring African American Women at Historically Black Colleges/Universities
Authors: Thomas Tammara Petrill , Maultsby Michelle Lee
Published: February 2018

This chapter describes how a considerable milestone for new faculty entering academia has been awarding tenure by the institution of higher education. This is often referred to as the Academy. Tenure-track faculty working towards tenure spend several years honing their craft in the areas of teaching, research, and service. Senior colleagues assume the lead in determining activities, and others who are considered authorities and leaders in the chosen field of scholarship. While HBCUs have provided an enormous source of support for African-American women who are tenure-track faculty, they continue to be underrepresented in the academy and are adversely impacted by the tenure process. Barriers that impede the tenure process of African-American women faculty include societal biases, stereotypes, systemic oppression, and lack of mentorship. This chapter seeks to provide awareness, discuss unique challenges specific to African American women faculty, and existing strategies to negotiating the tenure and promotion processes.
The Double-Edged Sword of “Othermothering” for African American Women Faculty With Families
Authors: Sawyer-Kurian Kyla Marie , Coneal Wanda B.
Published: February 2018

Historically Black Colleges or Universities (HBCUs) have historically been both vital and beneficial as they have educated, trained, and nurtured many African Americans throughout the years. Research indicates that there are some disparities between men and women faculty at HBCUs. The chapter will review research which discusses factors that may impact African American (AA) women faculty specifically AA women faculty with families (AAWFWF) within the academy at HBCUs. AA women faculty report spending a great amount of their time supporting, mentoring and nurturing students on academic and personal matters also called “othermothering.” While HBCUs have been a haven for students, some challenges and barriers arise for AAWFWF including bias toward caregiving, bias avoidance, unequal pay, collegial incivility, and difficulty maintaining work/life balance. Formal mentoring has been shown to be beneficial for AA faculty. Strategies to create a healthy environment for AAWFWF are presented and recommendations for an AAWFWF mentoring program at HBCUs are given.
Higher Education Pedagogy Revisited
Authors: McCarthy-Latimer Christopher
Published: February 2018

This chapter is an update that examines the effect of using “deliberation” as a tool for teaching at the college level. The students in this study considered the economic benefits and expenses of a box store. Deliberation provides a unique insight into what might be a better understanding of what students are thinking. The literature review contains various forms of deliberation including the process of deliberation in education; the outcomes of deliberative polling events; deliberation with technology; and whether working has an impact on students who deliberate. The use of pre- and posttest surveys shows that students who engaged in a deliberative dialogue were more likely to increase their civic learning and to change their opinions about the issues discussed. The findings demonstrate that deliberation pedagogy influences students' beliefs at both the individual and aggregate level.
Agriculture Livelihood Security
Authors: Nayak Sabyasachi
Published: February 2018

This chapter describes how through the prism of CSR, industry can take a stride in evolving its relationship with the stakeholders. Agriculture continues to remain the mainstay of livelihood for chunk of the population. The sector is drawn with the dual daunting challenges of producing more simultaneously without depleting natural resources. A pilot study is instituted to gain an insight into the CSR-agriculture initiative of the industry. This conceptual chapter has not attempted to triangulate the primary data, focusing on similar issues from other studies. However, the proposed 3D approach: “Diverse Dynamic Dignified,” is an outcome of FGD which provides a framework to take a broader view for wider replication by customizing it to the local conditions. This chapter contributes to the existing literature and advocates that the industry should prioritize agriculture livelihood security in their CSR endeavors.
Indigenous Knowledge as Resource to Sustain Self-Employment in Rural Development
Authors: Semali Ladislaus M.
Published: February 2018

This chapter explores the ways African rural youths and women seek opportunities to innovate and adapt indigenous knowledge as a locally developed resource of community resilience in the attempt to reduce household poverty. The two case groups discussed in this chapter engaged in self-employment enterprises. They drew upon their ecological and cultural knowledge, enabling themselves through shoestring budgets to sustain their livelihood and community wellbeing. The chapter shows that unemployment affects young people and rural women from all occupations and ethnic groups, a situation that puts them in a vulnerable and precarious living condition. The analysis showed that for most of youth found on the Tanzania's streets and urban municipalities, a secondary education has not proven useful in practical knowledge, skills, values or attitudes necessary to enter the world of work or to become self-employed.
Assessing the Social Media Presence and Activity of Major Greek Cities During 2014-2017
Authors: Karamagioli Evika , Staiou Eleni Revekka , Gouscos Dimitris
Published: February 2018

This chapter describes how little is known about how Greek local authorities capitalize on the potential of social media as a communication channel. The authors present the results of following up on a 2014 study assessing major Greek cities' presence on social media at the time. The authors check whether and how Greek cities may have improved their levels of acting and reacting via social media so as to identify eventual positive changes and/or patterns and discuss potential ways to implement comprehensive strategies for social media as civic interaction tools for local governments. A set of 52 major cities all over Greece (administrative capitals of the corresponding prefectures), has been chosen as the research population. Findings show that local authorities are advancing in the exploration of social media for communication with citizens, but have not yet reached a level at which they would use them as catalysts for citizen interaction in order to enhance civic engagement.
A Study to Analyze the Impact of the Sub-Prime Crisis on IPOs
Authors: Dubey Rakshita , Chandani Arti , Mehta Mita
Published: February 2018

The study of the IPOs are for a period of 10 years; hence, each company that came out with an IPO between 2004 and 2013 has been studied in terms of the paid up capital raised initially and then broken down into six sectors according to the type of industry they belong. The research is based on the assumption that the subprime crisis had a global effect and hence many developed countries suffered in terms of fall in exports, rise in debt defaults and reduced earrings of the corporate. However, the effect on India was minimal but the worldwide panic was there. The researchers have studied the impact of the subprime crisis on the IPOs issued during pre- and post-subprime crisis. The researchers have used statistical test to study the impact of subprime crisis on the Indian stock market. This compilation is a culmination of comprehensive in-depth study as well as practical experience.
Taxation and Elites in Central America
Authors: Garita Mauricio
Published: February 2018

The discussion of taxes in Central America has been based in economic and social crises. Because of these efforts, it is imperative to understand the history in order to understand the impact an economic crisis can have on taxes. Therefore, the study presents a research based on a historical approach with the purpose of understanding the different concepts concerning the elites and the evolution of the economic circumstances around it. Also, the discussion concerning inequality and development that evidence that not much has changed.
Information Security Management as a Business Strategy and Its Financial Impact
Authors: Mendoza Israel E.
Published: February 2018

The information security is importance as a strategic process to improve and maintain the continuity of the company. There have been developed various methodologies and risk management, safety guidelines information, however, does not go beyond operational and strategic part of business. Although some methodologies are based on international standards to implement controls to mitigate risks, but not the financial factors that could be impacted by these risks are analyzed. In some companies the legal aspect as a financial category, economic losses is not analyzed as a risk or information theft materializes. There are several methodologies based on guidelines and recommendations and provide general guidance on the management of information security; therefore, for purposes of this scientific research it will be taken into account some relevant points of those standards, which will undoubtedly help establish an appropriate risk methodology and subsequently to the definition of financial criteria for decision-making.
Telecommunications' Impact on Latin America's Economy
Authors: Cerezo Celso F.
Published: February 2018

The present chapter analyzes the importance of telecommunications and its economic effects by identifying the relation between the amount of telephone lines, both fixed and mobile, and the economy of Latin America as a region since year 1975 to 2015. The relation is demonstrated using a linear regression model. The case of Guatemala is analyzed in more in detail, where telecommunications have developed at an important pace since the privatization of the former public telco operator along crucial regulatory reforms.
The Negotiation and Effects of Fiscal Privileges in Guatemala
Authors: Garita Mauricio
Published: February 2018

The present chapter analyzes fiscal privileges in Guatemala from a taxation point of view, identifying the cost that they incur through the tax expenditure methodology. The chapter also discusses the historical situation of Guatemala concerning taxes and its consequence for the social situation and its relation. Therefore, the conclusion of this chapter is that fiscal privileges are politics aimed at minorities that cost more to the society than the benefits they have in Guatemala, as a consequence there is a sacrifice in taxation by benefiting certain sectors.
An Analysis on Fireworks Algorithm Solving Problems With Shifts in the Decision Space and Objective Space
Authors: Cheng Shi , Chen Junfeng , Qin Quande , Shi Yuhui
Published: February 2018

Fireworks algorithms for solving problems with the optima shifts in decision space and/or objective space are analyzed. The standard benchmark problems have several weaknesses in the research of swarm intelligence algorithms for solving single objective problems. The optimum shift in decision space and/or objective space will increase the difficulty of problem solving. Modular arithmetic mapping is utilized in the original fireworks algorithm to handle solutions out of search range. The solutions are implicitly guided to the center of search range for problems with symmetrical search range via this strategy. The optimization performance of fireworks algorithm on shift functions may be affected by this strategy. Four kinds of mapping strategies are compared on problems with different dimensions and different optimum shift range. From experimental results, the fireworks algorithms with mapping to the boundary or mapping to limited stochastic region obtain good performance on problems with the optimum shift. This is probably because the search tendency is kept in these two strategies.
Using Particle Swarm Optimization Algorithm as an Optimization Tool Within Developed Neural Networks
Authors: Klepac Goran
Published: February 2018

Developed neural networks as an output could have numerous potential outputs caused by numerous combinations of input values. When we are in position to find optimal combination of input values for achieving specific output value within neural network model it is not a trivial task. This request comes from profiling purposes if, for example, neural network gives information of specific profile regarding input or recommendation system realized by neural networks, etc. Utilizing evolutionary algorithms like particle swarm optimization algorithm, which will be illustrated in this chapter, can solve these problems.
Document Clustering
Authors: Patil Harsha , Thakur R. S.
Published: February 2018

As we know use of Internet flourishes with its full velocity and in all dimensions. Enormous availability of Text documents in digital form (email, web pages, blog post, news articles, ebooks and other text files) on internet challenges technology to appropriate retrieval of document as a response for any search query. As a result there has been an eruption of interest in people to mine these vast resources and classify them properly. It invigorates researchers and developers to work on numerous approaches of document clustering. Researchers got keen interest in this problem of text mining. The aim of this chapter is to summarised different document clustering algorithms used by researchers.
Linked Data, Towards Realizing the Web of Data
Authors: Zemmouchi-Ghomari Leila
Published: February 2018

Data play a central role in the effectiveness and efficiency of web applications, such as the Semantic Web. However, data are distributed across a very large number of online sources, due to which a significant effort is needed to integrate this data for its proper utilization. A promising solution to this issue is the linked data initiative, which is based on four principles related to publishing web data and facilitating interlinked and structured online data rather than the existing web of documents. The basic ideas, techniques, and applications of the linked data initiative are surveyed in this paper. The authors discuss some Linked Data open issues and potential tracks to address these pending questions.
A Decentralized Framework for Semantic Web Services Discovery Using Mobile Agent
Authors: Ben Seghir Nadia , Kazar Okba , Rezeg Khaled
Published: February 2018

Web services discovery provided by the UDDI registries is relatively primitive. It does not take into account the continuous growth in the number of services on the Web. The UDDI standard has been proposed and used for Web service publication and discovery. However, it does not allow users to choose the best provider. It does not offer a mechanism to choose a Web service based on its quality. The standard also lacks of sufficient semantic description in the content of Web services, this lack makes it difficult to find and compose suitable Web services during analysis, search, and matching processes. In addition, a central UDDI suffers from one centralized point problem and the high cost of maintenance. To get around these problems, the authors propose in this paper a novel framework based on mobile agent and metadata catalogue for Web services discovery. Their approach is based on user profile in order to discover appropriate Web services, meeting customer requirements, in less time and taking into account the QoS properties.
SWRLx
Authors: Bouaicha Souad , Boufaida Zizette
Published: February 2018

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.
Semantic Web-Based Framework for Scientific Workflows in E-Science
Authors: Vijayakumar Singanamalla , Dasari Nagaraju , Bhushan Bharath , Reddy Rajasekhar
Published: February 2018

In the future generation, computer science plays prominent role in the scientific research. The development in the field of computers will leads to the research benefits of scientific community for sharing data, service computing, building the frameworks and many more. E-Science is the active extending field in the world by the increase data and tools. The proposed work discusses the use of semantic web applications for identifying the components in the development of scientific workflows. The main objective of the proposed work is to develop the framework which assists the scientific community to test and deploy the scientific experiments with the help of ontologies, service repositories, web services and scientific workflows. The framework which aims to sustenance the scientific results and management of applications related to the specific domain. The overall goal of this research is to automate the use of semantic web services, generate the workflows, manage the search services, manage the ontologies by considering the web service composition.
Semantic Framework for an Efficient Information Retrieval in the E-Government Repositories
Authors: Martín Antonio , León Carlos
Published: February 2018

An enormous quantity of heterogeneous and distributed information is stored in e-government repositories. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. This chapter proposes a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. The authors suggest a conceptual architecture for a semantic search engine. They use case-based reasoning methodology to develop a prototype. OntoloGov is a collaborative effort that proposes a new form of interaction between citizens and e-government repositories, where the latter are adapted to users and their surroundings.
A Decision Support System (DSS) for Colorectal Cancer Follow-Up Program via a Semantic Framework
Authors: Passi Kalpdrum , Zhao Hongtao
Published: February 2018

This paper offers insights into evolving a decision support system (DSS) to aid primary care physicians and/or nurses in the post-surgical care of patients with Colorectal Cancer in a clinical setting. Presently, the oncologists in the cancer center, who are familiar with the Clinical Practice Guidelines (CPGs), are primarily responsible for the provision of follow-up care to their patients on the basis of the CPGs; in contrast, the attending primary care physician and/or nurse assisting the oncologist may be unfamiliar with these guidelines. These caregivers would, therefore, either require hardcopies of the CPGs or can be aided via a DSS for them to be able to provide the appropriate follow-up care for the respective cancer patients. Clearly, the Colorectal Cancer follow-up CPGs have to be analyzed and the ontology representing the knowledge embedded in the guidelines designed prior to realizing such a DSS. The designed ontology is often coded into Web Ontology Language (OWL) as a standard ontology that can be accessed through the Web. The authors' research team designed and presented the semantic framework of the web application, using the designed ontology that combines the current Web technology with database storage to achieve a unified development of the DSS. The authors also designed a user-friendly interface of the Web application to provide medical practitioners the functionality of the CPGs and the flexibility to customize the desired follow-up care schedule. The resulting DSS provides the physicians with follow-up program for the Colorectal Cancer patients based on the CPGs. The system was built using the semantic framework for the follow-up program and queries on the system are executed through SPARQL query engine.
Enhancing Visibility in EPCIS Governing Agri-Food Supply Chains via Linked Pedigrees
Authors: Solanki Monika , Brewster Christopher
Published: February 2018

Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of “linked pedigrees” - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.
Integration of Data Mining and Statistical Methods for Constructing and Exploring Data Cubes
Authors: Usman Muhammad
Published: February 2018

In high dimensional environments, the sheer size and volume of data poses a number of challenges in order to generate meaningful and informative data cubes. Data cube construction and exploration is a manual process in which analysts are required to visually explore the complex cube structure in order to find interesting information. Data cube construction and exploration has been dealt separately in the literature and in the past there has been very limited amount of work done which would guide the data warehouse designers and analysts to automatically construct and intelligently explore the data cubes. In the recent years, the combined use of data mining techniques and statistical methods has shown promising results in discovering knowledge from large and complex datasets. In this chapter, we propose a methodology that utilizes hierarchical clustering along with Principal Component Analysis (PCA) to generate informative data cubes at different levels of data abstraction. Moreover, automatically ranked cube navigational paths are provided by our proposed methods to enhance knowledge discovery from large data cubes. The methodology has been validated using real world dataset taken from UCI machine learning repository and the results show that the proposed approach assists in cube design and intelligent exploration of interesting cube regions.
To Implement an Open-MAS Architecture for Semantic Web Services Discovery
Authors: Gharzouli Mohamed , Derdour Makhlouf
Published: February 2018

Recently, several models have been proposed to design distributed and collaborative infrastructures for web services based systems. In this area, Peer-to-Peer (P2P) networks and Multi-Agents Systems offer many techniques for web services discovery and composition. However, both of the two combinations (P2P/web services and MAS/web services) have suffered from some problems. This article presents a generic P2P/MAS architecture for semantic web services discovery. It tries to merge these two distributed technologies and demonstrate how P2P networks can implement open-MAS architectures to build a collaborative distributed system. The main objective of this article is to find the most appropriate P2P protocol to make such systems. Before the presentation of the proposed architecture, it already presents a background of P2P categories and models. After, it chooses four different P2P protocols wherever it analyzes and discusses, for each one, the stabilization and traffic generation of the network.
The Role of Ontology Engineering in Linked Data Publishing and Management
Authors: Luczak-Rösch Markus , Simperl Elena , Stadtmüller Steffen , Käfer Tobias
Published: February 2018

In this article the authors evaluate the adoption and applicability of established ontology engineering results by the Linked Data providers' community. The evaluation relies on a combination of qualitative and quantitative methods; in particular, the authors conducted an analytical survey containing structured interviews with data publishers in order to give an account of the current ontology engineering practice in Linked Data provisioning, and compared and expanded our findings with statistics on ontology development and usage provided by the Billion Triple Challenges datasets from 2012 (using the vocab.cc platform) and from 2014 and other related tools. The findings of the evaluation allow data practitioners and ontologists to yield a better understanding of the conceptual part of the LOD Cloud; and form the basis for the definition of purposeful, empirically grounded guidelines and best practices for developing, managing and using ontologies in the new application scenarios that arise in the context of Linked Data.
Towards a Statistical Approach to the Analysis, the Indexing, and the Semantic Search of Medical Videoconferences
Authors: Yengui Ameni , Neji Mahmoud
Published: February 2018

In this article, the authors introduce their OSSVIRI information retrieval system which composed of three modules. In the analysis module, they have proposed a statistical technique exploiting the word frequency in order to extract the simple, compound and specific terms from the documents. In the indexing module, the authors used the ontology to associate the terms with their concepts, retrieve the relations between them and disambiguate the concepts to improve the sematic content of the documents. The concepts and relations are represented as a conceptual graph. In the research module, the authors have proposed a technique of users' query reformulation based on external resources and users' profiles and a technique of pairing based on the combined expansion of the requests and the documents guided by the context of the requirement in information and the documentary contents. This system is validated using the metrics from the research information and comparisons with existing statistical approach. The authors show that their approach achieves good results.
SPAM
Authors: Chauhan Ritu , Kaur Harleen
Published: February 2018

The tremendous increase in spatial database technology has created furious interest among the researchers to adopt new methodologies for discovery of interesting patterns among large databases. But the raw data gathered from various resources such as Geographic Information Systems (GIS), business organizations, medical databases, climatic, market survey, remote sensing and several other resources might consist of data, which can be relevant, irrelevant or noisy in nature. However, retrieval of patterns from such databases can lead to serious concerns, which can frame inconsistent or irrelevant futuristic results. To deal with such issues, feature selection techniques are adopted to remove irrelevant, redundant and noisy features. Our approach focuses on retrieval of effective and efficient spatial clusters from large number of medical databases. In this chapter, we have defined our novel framework SpaGrid and SPAM algorithm to retrieve clusters of variant shape and size from large databases. The application of our framework is used with spatial medical databases where the implementation details are discussed with Matlab 7.1.
Local and Global Latent Semantic Analysis for Text Categorization
Authors: Ghanem Khadoudja
Published: February 2018

In this paper the authors propose a semantic approach to document categorization. The idea is to create for each category a semantic index (representative term vector) by performing a local Latent Semantic Analysis (LSA) followed by a clustering process. A second use of LSA (Global LSA) is adopted on a term-Class matrix in order to retrieve the class which is the most similar to the query (document to classify) in the same way where the LSA is used to retrieve documents which are the most similar to a query in Information Retrieval. The proposed system is evaluated on a popular dataset which is 20 Newsgroup corpus. Obtained results show the effectiveness of the method compared with those obtained with the classic KNN and SVM classifiers as well as with methods presented in the literature. Experimental results show that the new method has high precision and recall rates and classification accuracy is significantly improved.
Systems Administration in Ontology-Based Applications
Authors: Alexandrova Assia , Iordanov Borislav , Abbas Syed , Upadrasta Phani , Sarasti Michael , Hilpold Thomas
Published: February 2018

A Citizen Relationship Management (OpenCiRM) system was built on a semantic web platform using model-driven development principles, to provide a government call center with operational agility and improved technical integration options. Business domain experts from municipal agencies administered the system by directly manipulating its ontology model. This paper highlights the new ontology engineering tasks and user roles that may emerge in organizations implementing the OpenCiRM system.
Automatic Schema-Independent Linked Data Instance Matching System
Authors: Nguyen Khai , Ichise Ryutaro
Published: February 2018

The goal of linked data instance matching is to detect all instances that co-refer to the same objects in two linked data repositories, the source and the target. Since the amount of linked data is rapidly growing, it is important to automate this task. However, the difference between the schemata of source and target repositories remains a challenging barrier. This barrier reduces the portability, accuracy, and scalability of many proposed approaches. The authors present automatic schema-independent interlinking (ASL), which is a schema-independent system that performs instance matching on repositories with different schemata, without prior knowledge about the schemata. The key improvements of ASL compared to previous systems are the detection of useful attribute pairs for comparing instances, an attribute-driven token-based blocking scheme, and an effective modification of existing string similarities. To verify the performance of ASL, the authors conducted experiments on a large dataset containing 246 subsets with different schemata. The results show that ASL obtains high accuracy and significantly improves the quality of discovered coreferences against recently proposed complex systems.
Bio-Inspired Private Information Retrieval System Over Cloud Service Using the Social Bees' Lifestyle With a 3D Visualisation
Authors: Bouarara Hadj Ahmed , Hamou Reda Mohamed , Abdelmalek Amine
Published: February 2018

In the last decade, a new paradigm had seen the light named Cloud Computing, which allows the delocalization of data and applications on a dematerialized infrastructure accessible from Internet. Unfortunately, the cloud services are facing many drawbacks especially in terms of security and data confidentiality. However, in a world where digital information is everywhere, finding the desired information has become a crucial problem. For the purpose to preserve the user privacy life new approaches and ideas had been published. The content of this chapter is a new system of bio-inspired private information retrieval (BI-PIR) using the lifestyle of social bees, which allows both to find and hid, the sensitive desired information. It is based on a multi-filters cryptosystem used by the server for the encryption of stored document and the retrieval model using a combination of filters by 3 types of workers bees (Purveyor, guardian and cleaner), the queen bee represents the query, and the hive represents the class of relevant documents. We have tested this system on the benchmark MEDLINE dataset with panoply of validation tools (recall, precision, f-measure, entropy, silence, noise, and accuracy) and a comparative study had been realized with other systems existed in literature. Finally, a 3D visualization tool had been developed in order to make the results in graphical format understandable by humans. Our objectives is to improve the services quality of cloud computing.
From Finding to Explaining
Authors: Dragos Valentina
Published: February 2018

Supporting anomaly analysis in the maritime field is a challenging problem because of the dynamic nature of the task: the definition of abnormal or suspicious behaviour is subject to change and depends on user interests. This paper provides a novel approach to support anomaly analysis in the maritime domain through the exploration of large collections of interpretation reports. Based on observables or more sophisticated patterns, the approach provides information retrieval strategies going from basic facts retrieval that guide short-term corrective actions to more complex networks of related concepts that help domain experts to understand or to explain abnormal vessel behaviours. Semantic integration is used to link various information sources, by using a commonly adopted standard. The paper seeks to explore different aspects of using information retrieval to support the analysis and interpretation of abnormal vessel behaviours for maritime surveillance.
Semantic Web Based Agricultural Information Integration
Authors: Ramar Kaladevi , Gurunathan Geetha
Published: February 2018

Huge volume of information is available in the WWW. However, the demand is on relevant information rather than available information, which are often heterogeneous and distributed. Agriculture is one such domain, which includes information like soil, crops, weather, etc., under one roof. This information is in different representations and structures e.g. weather. This scenario leads to a challenge that how to integrate the available and heterogeneous agricultural information to deliver better production. The information on the web is syntactically structured but, the need is to provide semantic linkage. The semantic web supports the existing web to easily process and interpret information. In this paper, a semantic based Agricultural Information System (AIS) is proposed which addresses heterogeneity issues among weather systems and integrates information like soil, weather, crop and fertilizers. AIS helps the farmers regarding the type of crop/soil, crop/climate, fertilizer applications, diseases and prevention methods using effective retrieval of information from integrated systems.
Semantic-Based Access Control for Data Resources in Open Grid Services Architecture - Data Access and Integration (OGSA-DAI)
Authors: Muppavarapu Vineela , Chung Soon M.
Published: February 2018

This paper proposes a semantic-based access control system for the data resources in the Open Grid Services Architecture - Data Access and Integration (OGSA-DAI). OGSA-DAI is a widely used middleware for integrating data resources in Grids. However, the identity-based access control in OGSA-DAI causes substantial overhead for the resource providers in virtual organizations (VOs), because the access control information of individual users has to be maintained by each resource provider. To solve these problems, the authors propose a semantic-based access control system using Shibboleth and ontology. Shibboleth, an attribute authorization service, is used to manage the user attributes, and the Web Ontology Language (OWL) is used to represent the ontology of the data resources and users. By using ontology, VOs can resolve the differences in their terminologies and specify access control policies based on concepts and user roles, instead of individual resources and user identities. As a result, the administration overhead of the resource providers is reduced considerably. In addition, the eXtensible Access Control Markup Language (XACML) is used to specify the access control policies uniformly across multiple VOs. The authors also developed an XACML policy administration tool that allows the administrators to create, update, and manage XACML policies. The performance analysis shows that our proposed system adds only a small overhead to the existing security mechanism of OGSA-DAI.
Multidimensional Ontology-Based Information Retrieval for Academic Counseling
Authors: Lam S. S. , Choi Samuel P. M.
Published: February 2018

Conventional information retrieval can only locate documents containing user specified keywords. Integrating domain ontology with information retrieval extends the keyword-based search to semantic search and thus potentially improves the precision and recall of the document retrieval. In this paper, a set of new multidimensional ontology-based information retrieval algorithms is proposed for searching both specific and related terms. In particular, the relevant data properties of an instance, the relevant concepts, the relevant related concepts, and the related instances of a given user query can be identified from the domain ontology via the multidimensional search. Using the proposed algorithms, an intelligent counselling system which provides 24x7 online academic counselling services is developed. Through an interactive user-interface and domain ontology, the system facilitates students to find desired information by reviewing and refining their query. The article also outlines how to enable ontology-based searching for a conventional website.
Context-Aware Presentation of Linked Data on Mobile
Authors: Costabello Luca , Gandon Fabien
Published: February 2018

In this paper the authors focus on context-aware adaptation for linked data on mobile. They split up the problem in two sub-questions: how to declaratively describe context at RDF presentation level, and how to overcome context imprecisions and incompleteness when selecting the proper context description at runtime. The authors answer their two-fold research question with PRISSMA, a context-aware presentation layer for Linked Data. PRISSMA extends the Fresnel vocabulary with the notion of mobile context. Besides, it includes an algorithm that determines whether the sensed context is compatible with some context declarations. The algorithm finds optimal error-tolerant subgraph isomorphisms between RDF graphs using the notion of graph edit distance and is sublinear in the number of context declarations in the system.
Augmenting User Interaction Experience Through Embedded Multimodal Media Agents in Social Networks
Authors: Matsiola Maria , Dimoulas Charalampos , Kalliris George , Veglis Andreas A.
Published: February 2018

The current chapter proposes media agent and multi-agent models aiming at improving mediated communication and information exchange in social networking. Great progress has been conducted during the last decades in Information and Communication Technologies, which is also reflected in social media. The proposed models exploit the latest media technologies for the augmentation of user-interaction and contribution experience in multiple levels. Features of the suggested agent and multi-agent approaches are discussed and elaborated through the prism of social computing, social media analytics and intelligence, resulting to a sophisticated communication mediator between users and social groups. In addition, enhanced user engagement and collaboration are considered in terms of rich media experience and augmented reality, semantic interaction services, intelligent content processing and management automation over interoperable multiplatform environments. Social media cooperation and integration is envisioned towards the realization of Web 3.0 and beyond, as the main chapter contribution.
Semantic Retrieval of Documents From Digital Repositories and Twitter Integration in the Moodle Environment
Authors: Rodrigues de Oliveira Renan , Costa Fábio Moreira , Luiz de Carvalho Cedric , Ambròsio Ana Paula
Published: February 2018

Virtual learning environments represent an important step in enabling distance and blended education. Moodle's structure for content enables the identification of well-defined learning contexts. Nevertheless, Moodle currently does not provide standard features to leverage the use of such contextual information, nor does it provide a standard built-in search facility. This chapter presents a context-sensitive Moodle plug-in for the search of external resources that allows semantic-based retrieval of documents from any external repository that offers an OAI-PMH standard compliant interface. As a way to increase their potential use, the plug-in also retrieves Twitter messages (known as tweets), since social networks are shown as an important tool to support education. Retrieved resources are presented in order of importance according to both the query terms provided by the user and the current context derived from the Moodle content structure. Searches are semantically expanded by evaluating the query terms according to a specific ontology associated with the context.