waashk/dblp huggingface dataset:
a methodology for comparing classifiers that allow the control of bias. this paper presents false positive-critical classifiers comparison a new technique for pairwise comparison of classifiers that allow the control of bias. an evaluation of na&iuml;ve bayes, k-nearest neighbour and support vector machine classifiers has been carried out on five datasets containing unsolicited and legitimate e-mail messages to confirm the advantage of the technique over receiver operating characteristic curves. the evaluation results suggest that the technique may be useful for choosing the better classifier when the roc curves do not show comprehensive differences, as well as to prove that the difference between two classifiers is not significant, when roc suggests that it might be. spam filtering is a typical application for such a comparison tool, as it requires a classifier to be biased toward negative prediction and to have some upper limit on the rate of false positives. finally the particular evaluation summary is presented, which confirms that support vector machines out-perform other methods in most cases, while the na&iuml;ve bayes classifier works well in a narrow, but relevant range of false positive rate.
abstract non-interference in a fragment of java bytecode. this work presents a program analyzer for checking abstract non-interference in a fragment of java bytecode. abstract non-interference is an information flow property which is weaker and more general than standard non-interference, since it can allow some selected parts of secret information to flow into the public part of a program. the motivation for such a weakening is that some flows are indeed useful in real-life applications. the amount of allowed flows is encoded into abstract domains, which characterize the degree of precision of a potential attacker in observing data; flows are forbidden as long as they can be observed and exploited by attackers. abstract values describe possible values of programs in different executions. basic features of java bytecode are considered; advanced topics, such as method calls, objects and exceptions, are also discussed. a program is said to be secure if analysis computes a state which does not contain private information in public places; information flows can exist only as long as the attacker has not enough observational power to see and exploit them.
unsupervised learning techniques for an intrusion detection system. with the continuous evolution of the types of attacks against computer networks, traditional intrusion detection systems, based on pattern matching and static signatures, are increasingly limited by their need of an up-to-date and comprehensive knowledge base. data mining techniques have been successfully applied in host-based intrusion detection. applying data mining techniques on raw network data, however, is made difficult by the sheer size of the input; this is usually avoided by discarding the network packet contents.in this paper, we introduce a two-tier architecture to overcome this problem: the first tier is an unsupervised clustering algorithm which reduces the network packets payload to a tractable size. the second tier is a traditional anomaly detection algorithm, whose efficiency is improved by the availability of data on the packet payload content.
recommendation-based browsing assistance for corporate knowledge portals. the management of knowledge, i.e. knowing what is known and the ability to exploit it is a burning issue for most organizations. though knowledge management has a strong social perspective, information technology supports knowledge management strategies by providing tools that store codified knowledge and allow its retrieval. the value of knowledge management derives from the wide use of the stored knowledge, its annotation and refinement as well as its application in business practices. we support this issue of information browsing and retrieval by adapting and applying recommendation technology to reduce access barriers towards corporate knowledge portals. for this purpose we exploit domain heuristics to improve collaborative filtering techniques in order to cope with the problem of low numbers of users the knowledge portals have.
dynamically generating web application fragments from page templates. web-based applications are typically required to be highly customizable and configurable. new application requirements have to be introduced rapidly, often without stopping the running application process. moreover, in many cases the same business logic has to be presented to different channels and/or user interfaces. in this paper we present a dynamic page template architecture for decomposing configurable and representational fragments of the application from the business logic. page templates consist of static xml files and of dynamic class definitions. the xml-based page templates can be used for declarative definitions of configurable fragments, say, by the end-user with a graphical tool. the page template classes can be used for behavior specification, say, for defining common styles of decoration of the presented pages. both parts are dynamically loaded into the web application environment and composed with the web objects. thus, the configurable and representational fragments of web objects are dynamically generated from the changeable and extensible descriptions in the page templates. the concepts presented are applied in various larger software systems. we will present a highly customizable conference management system as an example case.
statistical buffering for streaming media data access in a mobile environment. streaming media (e.g., music or video) data access has been a research problem over the past few years, and the problem becomes tougher when the clients are mobile devices whose limited storage spaces prevent the clients from holding a large cache. a practical solution for the cellular system is to buffer the streaming data on the base stations, serving as the "cache" to the mobile devices. however, when mobile devices move from one cell to another, the cached data should also be migrated to the corresponding base station in order that users can view the media smoothly. when the number of requests increases, stations may face heavy data migration and storage burden. in this paper, we propose a statistical buffering mechanism by adapting saa search which makes use of prior knowledge (statistical data) to predict the trend of user movement among cells. experimental studies show that, with an acceptable complexity, our algorithms can obtain good performance on buffering streaming media data.
migration to web services oriented architecture: a case study. the rapid emerging of web-services technology is dramatically changing the scenario of web application design and development. this paper presents a web-services oriented architecture. as a case study, the paper reports on an on-going project on the design and development of a pass-through authentication web-services for on-line electronic payment applications. this is a first step towards an electronic payment web-service.
towards increasing web application productivity. in this paper we present and discuss a template/meta-data based partial code generation system supporting web application development. seamlessly incorporating the recent top-notch technologies, the framework maximally exploits the capabilities of the underlying implementation technologies. our approach primarily benefits the framework and code developers. in addition, the complete separation of data model, navigation model, and presentation model reflects on a more general conceptual process that would decouple the technique and methodology from its underlying technology choices. the decoupling between the generated code and the code that is necessarily added later on through other development pathways than the generator deals with the incremental changes and adaptations of the models in the face of an operational system, therefore further enhances the extensibility, maintainability, and reusability of the generated applications.
spatial geometric constraint solving based on k-connected graph decomposition. we propose a geometric constraint solving method based on connectivity analysis in graph theory, which can be used to decompose a well-constrained problem into some smaller ones if possible. we also show how to merge two rigid bodies if they share two or three geometric primitives in a bi-connected or tri-connected graph respectively. based on this analysis, problems similar to the "double banana problem" could be easily detected.
a tabu search algorithm for the safe transportation of hazardous materials. in this work, we study the problem of the safe transportation of hazardous materials, which is an important operational problem and has been studied extensively in the literature. we outline previous work and propose a new model that is a variant of the vehicle routing problem with time windows (vrptw). the objective is to find a schedule to guarantee the safety of all vehicles. we propose a tabu search (ts) heuristic with a dynamic penalty mechanism to obtain good solutions. a realistic data generation mechanism is also presented and the elaborate computational results show the strengths of our algorithms.
ubidata: ubiquitous mobile file service. one of the most challenging objectives of mobile data management is the ubiquitous, any time, anywhere access. this objective is very difficult to meet due to several network and mobile device limitations. optimistic data replication is a generally agreed upon approach to alleviating the difficulty of data access in the adverse mobile environment. however, the two currently most popular models, both client/server and peer-to-peer models, do not adequately meet the ubiquity objectives. in our views, mobile data management should adequately support access to any data source, from any mobile device. it should also eliminate user involvement by automating data selection, hoarding, and synchronization, regardless of the mobile device chosen by the user. in this paper, we present ubidata: an application-transparent, double-middleware architecture that addresses these challenges. ubidata supports access and update to data from heterogeneous sources (e.g. files belonging to different file systems). it provides for the automatic and device-independent selection, hoarding, and synchronization of data. we present the ubidata architecture and system component, and evaluate the effectiveness of ubidata's automatic data selection and hoarding mechanisms.
personalization and visualization on handheld devices. the small screen size of handheld mobile devices poses an inherent problem in visualizing data: very often it is too difficult and unpleasant to navigate through the plethora of presented information. this paper presents a novel approach to personalized and adaptive content presentation for handheld devices, which has been implemented in a mobile financial application system based on a 3-tier architecture. the approach is independent of wireless networks and mobile devices. it utilizes a combination of user profiling, data clustering, and visualization techniques (fisheye and semantic zooming), enhancing the understandability of the data and improving the usability of the device.
an attribute-based access matrix model. in traditional access control models like mac, dac, and rbac, authorization decisions are determined according to identities of subjects and objects, which are authenticated by a system completely. modern access control practices, such as drm, trust management, and usage control, require flexible authorization policies. in such systems, a subject may be only partially authenticated according to one or more attributes. in this paper we propose an attribute-based access matrix model, named abam, which extends the access matrix model. we show that abam enhances the expressive power of the access matrix model by supporting attribute-based authorizations. specifically, abam is comprehensive enough to encompass traditional access control models as well as some usage control concepts and specifications. on the other side, expressive power and safety are two fundamental but conflictive objectives in an access control model. we study the safety property of abam and conclude that the safety problem is decidable for a restricted case where attribute relationships allow no cycles. the restricted case is shown to be reasonable enough to model practical systems.
privacy preserving learning in negotiation. machine learning techniques are widely used in negotiation systems. to get more accurate and satisfactory learning results, negotiation parties have the desire to employ learning techniques on the union of their past negotiation records. however, negotiation records are usually confidential and private, and owners may not want to reveal the details of these records. in this paper, we introduce a privacy preserving negotiation learning scheme that incorporate secure multiparty computation techniques into negotiation learning algorithms to allow negotiation parties to securely complete the learning process on a union of distributed data sets. as an example, a detailed solution for secure negotiation q-learning is presented based on two secure multiparty computations: weighted mean and maximum. we also introduce a novel protocol for the secure maximum operation.
a fast and effective steganalytic technique against jsteg-like algorithms. detection of hidden messages in images, also known as image steganalysis, is of great significance to network information security. in this paper, we propose a fast and effective steganalytic technique based on statistical distributions of dct coefficients which is aimed at two kinds of popular jsteg-like steganographic systems, sequential jsteg and random jsteg for jpeg images. our approach can not only determine the existence of hidden messages in jpeg images reliably, but also estimate the amount of hidden messages exactly. its advantages also include simplicity, computational efficiency and easy implementation of real-time detection. experiment results show the superiority of our approach over other steganalytic techniques.
effort and accuracy analysis of choice strategies for electronic product catalogs. one crucial task for e-commerce systems is to help buyers find products that not only satisfy their preferences but also reduce their search effort. usually the amount of available products is far beyond the upper limit that any individual could process by hand; thus product search tools are employed to generate target product (s) by eliciting the buyer's preferences and then executing some kind of choice strategies. we propose in this paper an extended effort-accuracy framework for measuring the performance of various choice strategies in terms of cognitive effort, elicitation effort and decision accuracy. the performance of a variety of basic choice strategies is further studied by theoretical analysis as well as empirical simulations. it shows that the performance of a given choice strategy is a tradeoff between choice accuracy and effort required from the users. the proposed framework also suggests a new efficient method of evaluating the user interfaces of e-commerce systems by analyzing the performance of the underlying choice strategies.
an efficient implementation of parametric line and polygon clipping algorithm. an improved parametric line clipping algorithm is presented. the line clipping algorithm is extended to polygon clipping. the implementations of both the algorithms are novel and outperform many previous algorithms in the literature. this is supported by theoretical consideration and experimental results on randomly selected lines and polygons. the algorithms are implemented in java. the java applet allows the user to visualize the experimental results by comparing the existing algorithms and the new algorithms.
a decision-theoretic approach for designing proactive communication in multi-agent teamwork. techniques that support effective communication during teamwork processes are of particular importance. psychological study shows that an effective team often can anticipate information exchange among the team and communicate relevant information proactively. proactive communication is crucial for understanding and sharing common goals and for cooperative actions. communication can be valuable if it assists agents with new and timely information; it also has cost because it consumes network resources such as bandwidth. to address these issues, we present a new model that uses information production and need to capture the complex multi-agent communication process and a dynamic decision-theoretic determination of communication strategies. we also introduce a generic utility function and an algorithm, dtpc (decision-theoretic proactive communication), that focuses on representing information production and need of team members and resolving decision interactions among them for making decisions.
applying agent technology to software process modeling and process-centered software engineering environment. the software processes can be analyzed, designed, and maintained as if it is a piece of software. this view enables the application of software engineering technologies to software process modeling (spm) and process-centered software engineering environment (psee). one reason for the relatively few applications of spms and psees technologies in the software industry is that traditional software engineering technologies applied to the spms and psees are not suitable for modeling software processes which are human-centered. this paper proposes an approach for applying agent technology, which has been accepted as a novel software engineering paradigm, to spm and psee. in this approach, software processes are viewed as the collaboration of a group of process agents that know how to manage the software development activities and can act in the way software developers go about planning, enacting and reflecting on their work. an agent-based psee for enacting software processes under the proposed approach is also given in this paper.
selecting the best valid scopes for wireless dissemination of location-dependent data. mobility of user poses new challenges to research on spatial data access. spatial data cached in the mobile client may become invalid because of the movement of the client. to increase the reusability of the cached data, we can identify the valid scope of the spatial data (i.e., the spatial area within which the data is known to be valid) and save the valid scope as well as the data in the cache. in this paper, we study issues on the dissemination of spatial data and valid scopes in a wireless environment. we investigate methods for representing valid scopes and their impacts on system performance. a generic representation method, called the invalidation-efficiency-based (ieb) method, is proposed. simulation experiments are conducted to compare the performance of ieb with other representation methods. result shows that ieb is superior to the other methods because it tries to balance the precision and overhead of valid scopes.
node clustering based on link delay in p2p networks. peer-to-peer (p2p) has become an important computing model because of its adaptation, self-organization and autonomy etc. but efficient organization of the nodes in p2p networks is still a challenge needs to be addressed. node clustering is a mechanism that aims to provide an optimal infrastructure to organize the nodes in a p2p network. this paper describes an approach to implement node clustering based on link delay of node communications in the p2p network. this approach is completely distributed, in which each node only depends on its neighbors to implement node clustering. in this approach, we propose two distributed algorithms: t-closure algorithm and hierarchical node clustering algorithm to find node clusters automatically in a p2p network. we explore the node connectivity together with the connection quality. as a result, the link delay of communication between the super-node and the peer-node in node clustering can be limited, which will improve the overall performance of p2p networks.
dynamic interactive spatial similarity retrieval in iconic image databases using enhanced digraph. similarity-based retrieval of images is an important task in many image database applications. interactive similarity retrieval is one way to resolve the fuzzy area involving psychological and physiological factors of individuals during the retrieval process. a good interactive similarity system is not only dependent on a good measure system, but also closely related to the structure of the image database and the retrieval process based on the respective image database structure. in this paper, we propose to use a dynamic similarity measure on top of the enhanced digraph index structure for interactive iconic image similarity retrieval. our approach makes use of the multiple feedbacks from the user to get the hidden subjective information during the retrieval process, and avoids the high cost of re-computation of an interactive retrieval algorithm.
approaches to text mining for clinical medical records. clinical medical records contain a wealth of information, largely in free-text form. means to extract structured information from free-text records is an important research endeavor. in this paper, we describe a medical information extraction (medie) system that extracts and mines a variety of patient information with breast complaints from free-text clinical records. medie is a part of medical text mining project being conducted in drexel university. three approaches are proposed to solve different ie tasks and very good performance (precision and recall) was achieved. a graph-based approach which uses the parsing result of link-grammar parser was invented for relation extraction; high accuracy was achieved. a simple but efficient ontology-based approach was adopted to extract medical terms of interest. finally, an nlp-based feature extraction method coupled with an id3-based decision tree was used to perform text classification.
regularized b-spline network and its application to heart arrhythmia classification. this paper presents an effective learning scheme that combines b-spline modeling and regularized neural networks. essential issues of structural design and learning process are discussed. regularization theory is leveraged to design the topological structure of the network. a training algorithm is derived for the learning of both synaptic weights and b-spline coefficients. the approach is then applied to the medical problem of heart arrhythmia detection, particularly the detection of premature ventricular contraction. promising results demonstrate the potential benefits of the proposed method.
boundary extraction in thermal images by edge map. extracting object boundaries in thermal images is a challenging task because of the amorphous nature of the images and the lack of sharp boundaries. classical edge-based segmentation methods have the drawback of not connecting edge segments to form a distinct and meaningful boundary. many level set approaches, which can deal with changes of topology and the presence of corners, have been developed to extract object boundaries. previous researchers have used image gradient, edge strength, area minimization and region intensity to define the speed function. our approach uses edge direction and magnitude, called an edge map, as the main component of the speed function. the edge map points toward the nearest boundary; its magnitude represents the total gradient energy in the half plane. the experimental results are significantly superior to those obtained using edge magnitude alone.