ppxscal/embedding_network huggingface dataset:
Needs-Centric Searching and Ranking Based on Customer Reviews
Authors: Thomas Y. Lee, Simon Li, Ran Wei
Venue: Proceedings of the 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services (2008)

Online retailers have associated the introduction of user-generated product reviews with increased customer sales and decreased product returns. For all of the perceived value conveyed by customer reviews, however, little effort has been directed towards leveraging user-generated content beyond a productcentric focus: customers first select a product in order to read from prior users of that product. In this paper, we integrate traditional information retrieval relevance ranking with database aggregation to model the knowledge within online product reviews and product descriptions. Customers search the knowledge base of reviews by querying on specific needs or interests. The result is a customized ranking of products, a recommendation list that is based upon and explained by the text of reviews written by prior users expressing similar needs or interests. We evaluate the approach using a knowledge base of online reviews from Epinions.com and compare results to expert recommendations from Consumer Reports.
A Novel Spatio-Temporal Attributes Index Based Query for Wireless Sensor Networks
Authors: Weiguo Wu, Heng Chen, Yong Wu, Yi Liu
Venue: International Journal of Distributed Sensor Networks (2009)

Wireless sensor networks (WSNs) are envisioned to consist of hundreds to thousands of wireless sensor nodes. The operator doesn't interest in the data sensed by a specific sensor node generally, on the contrary, he pays more attention to the data gathered from a specific area in granted time. One crucial problem is how to process the great deal of data and respond to the query request. We propose a novel query processing based data attributes, called Spatio-Temporal Attributes R-tree based Query (STARQ). Consider the similarity of data collected by a sensor node and its neighboring nodes, partial clustering algorithm is used to form a storage cluster. Partial clustering algorithm is implemented in two phases. First phase is the beginning of partial clustering, in which an object occurs. In second phase, a certain node (e.g., resumes from failure) senses an existed object. The method provided in this paper aims to obtain the neighboring nodes firstly, and judges whether existing a storage cluster that conforms to metadata of the sensor node or not. If the relevant storage cluster does not exist, first phase works, otherwise second phase. If failed in first phase, partial clustering algorithm is called again after a random time. If there are more than one relevant storage cluster in second phase, exercises a sort algorithm which is in descending order according to the storage node's capability weight, and tries to join a storage cluster in turn. R-tree [1] is an approximately balanced search tree that is widely used to handle spatial data in traditional database systems. Motivated by the unique characteristic of R-tree, a Saptio-Temporal Attributes R-tree (STAR) is built on the top of storage clusters. Objects in STAR are not restricted to the geographical rectangles and could be any abstract ranges of arbitrary attributes. A top-down approach that achieves energy efficiency is adopted to locate the corresponding storage nodes, which transmit the relevant data back to the operator. We compare STARQ with Directed Diffusion [2] and GHT [3] in NS-2. To measure the performance of these protocols, we consider two metrics: interval of query and the size of network. The simulation results show that STARQ has better performance with different query intervals and network size.
The comparisons of prognostic indexes using data mining techniques and Cox regression analysis in the breast cancer data
Authors: Mevlut Ture, Fusun Tokatli, Imran Kurt Omurlu
Venue: Expert Systems with Applications: An International Journal (2009)

The purpose of this study is to determine new prognostic indexes for the differentiation of subgroups of breast cancer patients with the techniques of decision tree algorithms (C&RT, CHAID, QUEST, ID3, C4.5 and C5.0) and Cox regression analysis for disease-free survival (DFS) in breast cancer patients. A retrospective analysis was performed in 381 breast cancer patients diagnosed. Age, menopausal status, age of menarche, family history of cancer, histologic tumor type, quadrant of tumor, tumor size, estrogen and progesterone receptor status, histologic and nuclear grading, axillary nodal status, pericapsular involvement of lymph nodes, lymphovascular and perineural invasion, adjuvant radiotherapy, chemotherapy and hormonal therapy were assessed. Based on these prognostic factors, new prognostic indexes for C&RT, CHAID, QUEST, ID3, C4.5 and C5.0 and Cox regression were obtained. Prognostic indexes showed a good degree of classification, which demonstrates that an improvement seems possible using standard risk factors. We obtained that C4.5 has a better performance than C&RT, CHAID, QUEST, ID3, C5.0 and Cox regression to determine risk groups using Random Survival Forests (RSF).
Comparing of feedback-collection and think-aloud methods in program comprehension studies
Authors: Amela Karahasanovic, Unni Nyhamar Hinkel, Dag I. K. Sjøberg, Richard Thomas
Venue: Behaviour & Information Technology (2009)

This paper reports an explorative experimental comparison of (i) an experience-sampling method called feedback collection and (ii) the think-aloud methods with respect to their usefulness in studies on program comprehension. Think-aloud methods are widely used in studies of cognitive processes, including program comprehension. Alternatively, as in the feedback-collection method (FCM), cognitive processes can be traced by collecting written feedback from the subjects at regular intervals. We compare FCM with concurrent think-aloud (CTA) and retrospective think-aloud (RTA) regarding type and usefulness of the collected information, costs related to analysis of the collected information and effects of the data collection methods on the subjects' performance. FCM allowed us to identify a greater number of comprehension problems that prevented progress or caused significant delay (FCM: 30 problems; CTA: 5; RTA: 15). It was less precise in identifying strategies for comprehension than CTA (92% correctness for FCM; 100% for CTA). FCM was less expensive in analysis (transcription and coding) than the other two methods (FCM: 0.7 h of analysis per protocol; CTA: 31 h; RTA: 7.9 h). The results indicate that all three methods of data collection were intrusive and affected the performance of the subjects with respect to time and correctness (small to medium effect size). This research confirms that FCM can be used beneficially in studies that trace the cognitive processes involved in, and identify problems related to, the comprehension of software applications. On the basis of our experience, we recommend that FCM be used in studies that have a large number of subjects and as a complement to other methods for tracing cognitive processes, such as user log files. We recommend a design with two groups (verbalisation and silent control) and a pretest task to be used in studies with FCM or CTA that focus on performances.
Mixed-signal simulation challenges and solutions
Authors: Henry Chang, William Walker, John G. Maneatis, John Croix
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

The design of complex mixed-signal system-on-a-chip (SOC) designer poses challenging requirements on the simulation design environment. The simulation platform has to include simulations at the behavioral, gate and transistor-level which have traditionally been done in separate environments. As the scaling trend continues, the designer needs additional accuracy and capacity, new capabilities such as efficient statistical simulation that takes into account layout dependent effects. In this panel we have representatives from the CAD and design community discussing the challenges and current solutions available to the mixed-signal simulation challenge.
xCrawl: A High-Recall Crawling Method for Web Mining
Authors: Kostyantyn Shchekotykhin, Dietmar Jannach, Gerhard Friedrich
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

Web Mining Systems exploit the redundancy of data published on the Web to automatically extract information from existing web documents. The first step in the Information Extraction process is thus to locate within a limited period of time as many web pages as possible that contain relevant information, a task which is commonly accomplished by applying focused crawling techniques. The performance of such a crawler can be measured by its "recall", i.e. the percentage of documents found and identified as relevant compared to the number of existing documents. A higher recall value implies that more redundant data is available, which in turn leads to better results in the subsequent fact extraction phase. In this paper, we propose xCrawl, a new focused crawling method which outperforms state-of-the-art approaches with respect to recall values achievable within a given period of time. This method is based on a new combination of ideas and techniques used to identify and exploit navigational structures of websites, such as hierarchies, lists or maps. In addition, automatic query generation is applied to rapidly collect web sources containing target documents. The proposed crawling technique was inspired by the requirements of a Web Mining System developed to extract product and service descriptions and was evaluated in different application scenarios. Comparisons with existing focused crawling techniques reveal that the new crawling method leads to a significant increase in recall whilst maintaining precision.
A Note on the Effects of Service Time Distribution in the M/G/1 Queue
Authors: Alexandre Brandwajn, Thomas Begin
Venue: Proceedings of the 2009 SPEC Benchmark Workshop on Computer Performance Evaluation and Benchmarking (2009)

The M/G/1 queue is a classical model used to represent a large number of real-life computer and networking applications. In this note, we show that, for coefficients of variation of the service time in excess of one, higher-order properties of the service time distribution may have an important effect on the steady-state probability distribution for the number of customers in the M/G/1 queue. As a result, markedly different state probabilities can be observed even though the mean numbers of customers remain the same. This should be kept in mind when sizing buffers based on the mean number of customers in the queue. Influence of higher-order distributional properties can also be important in the M/G/1/K queue where it extends to the mean number of customers itself. Our results have potential implications for the design of benchmarks, as well as the interpretation of their results.
A stable clustering algorithm for mobile ad hoc networks based on attractor selection
Authors: Gen Nishikawa, Fukuhito Ooshita, Hirotsugu Kakugawa, Toshimitsu Masuzawa
Venue: Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems (2008)

With the spread of wireless technology, mobile ad hoc networks is getting increased attention in recent years. In mobile ad hoc networks, network topologies dynamically change because of node mobility. Thus, it is important to design an algorithm that has strong stability against frequent topology changes. Attractor selection is one of the biologically inspired approaches that have strong stability against environmental changes. In this paper, we propose a stable clustering algorithm based on attractor selection for mobile ad hoc networks. Clustering is a fundamental problem for distributed systems and makes it easy to manage large scale networks. We show the effectiveness of our algorithm by simulations.
Translation of Timed Promela to Timed Automata with Discrete Data
Authors: Wojciech Nabiałek, Agata Janowska, Paweł Janowski
Venue: Fundamenta Informaticae (2008)

The aim of the work is twofold. In order to face the problem of modeling time constraints in Promela, a timed extension of the language is presented. Next, timed Promela is translated to timed automata with discrete data, that is timed automata extended with integer variables. The translation enables verification of Promela specifications via tools accepting timed automata as input, such as VerICS or Uppaal. The translation is illustrated with a well known example of Fischer's mutual exclusion protocol. Some experimental results are also presented.
Preparation of Nd: YAG powder by sol-gel method in comparing with solid state reaction
Authors: Jahangir Hasani Barbaran, Fereshteh Hajiesmaeilbaigi
Venue: Proceedings of the 6th conference on Microelectronics, nanoelectronics, optoelectronics (2007)

Nd:YAG powder was synthesized by sol-gel method and compared with solid state reaction method. The XRD patterns of the heated powders at 900° C showed the single phase of YAG is formed. By SEM, micrographs of the synthesized samples and also homogeneity of Nd distribution in the YAG lattice was observed.
Corepresentation of a sylow p-subgroup of a group Sn
Authors: R. V. Skuratovsky
Venue: Cybernetics and Systems Analysis (2009)

The corepresentation of a Sylow p-subgroup of a symmetric group in the form of generating relations is investigated, and a Sylow subgroup of a group $\rm{S_{p^k}}$ , i.e., an n-fold wreath product of regular cyclic groups of prime order, that is isomorphic to the group of automorphisms of a spherically homogeneous root tree is also studied.
Understanding why we preserve some things and discard others in the context of interaction design
Authors: William Odom, James Pierce, Erik Stolterman, Eli Blevis
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

This paper takes up the problem of understanding why we preserve some things passionately and discard others without thought. We briefly report on the theoretical literature relating to this question, both in terms of existing literature in HCI, as well as in terms of related literatures that can advance the understanding for the HCI community. We use this reading to refine our frameworks for understanding durability in digital artifice as an issue of sustainable interaction design in HCI. Next, we report in detail on our ongoing work in collecting personal inventories of digital artifice in the home context. We relate our prior and most current personal inventories collections to the framework that owes to our reading of the theoretical literature. Finally, we summarize the theoretical implications and findings of our personal inventories work in terms of implications for the design of digital artifice in a manner that is more durable.
Iterative disparity estimation and image segmentation
Authors: Marcos Alexandre Amador Medeiros, Luis Alberto Da Silva Cruz
Venue: Proceedings of the 8th conference on Signal processing, computational geometry and artificial vision (2008)

In multiview video analysis, disparity estimation and image segmentation are important tasks. This paper presents an iterative method that uses segmentation and disparity information in order to create a synthesized predictive video. The frames are initially segmented and the segments applied in a disparity estimation process. Following an error analysis is made searching for incorrect disparity values. The result disparity map is used to improve the segmentation, initiating another iteration cycle, or to create the intermediate synthesized view.
hiCUDA: a high-level directive-based language for GPU programming
Authors: Tianyi David Han, Tarek S. Abdelrahman
Venue: Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units (2009)

The Compute Unified Device Architecture (CUDA) has become a de facto standard for programming NVIDIA GPUs. However, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host memory and various components of the GPU memory, and of manually optimizing the utilization of the GPU memory. Practical experience shows that the programmer needs to make significant code changes, which are often tedious and error-prone, before getting an optimized program. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. Nonetheless, it supports the same programming paradigm already familiar to CUDA programmers. We have prototyped a source-to-source compiler that translates a hiCUDA program to a CUDA program. Experiments using five standard CUDA bechmarks show that the simplicity and flexibility hiCUDA provides come at no expense to performance.
A novel method for speckle noise reduction and ship target detection in SAR images
Authors: Shi-qi Huang, Dai-zhi Liu, Gui-qing Gao, Xi-jian Guo
Venue: Pattern Recognition (2009)

It is very difficult to detect small targets when the scattering intensity of background clutter is as strong as the targets and the speckle noise is serious in synthetic aperture radar (SAR) images. Because the scattering of man-made objects lasts for a longer time than that of background clutter in azimuth matching scope, it is much easier for man-made objects to produce strong coherence than ground objects. As the essence of SAR imaging is coherent imaging, the contrast between targets and background clutter can be enhanced via coherent processing of SAR images. This paper proposes a novel method to reduce speckle noise for SAR images and to improve the detected ratio for SAR ship targets from the SAR imaging mechanism. This new method includes the coherence reduction speckle noise (CRSN) algorithm and the coherence constant false-alarm ratio (CCFAR) detection algorithm. Real SAR image data is used to test the presented algorithms and the experimental results verify that they are feasible and effective.
Lparse Programs Revisited: Semantics and Representation of Aggregates
Authors: Guohua Liu, Jia-Huai You
Venue: Proceedings of the 24th International Conference on Logic Programming (2008)

Lparse programs are logic programs with weight constraints as implemented in the smodels system, which constitute an important class of logic programs with constraint atoms. To effectively apply lparse programs to problem solving, a clear understanding of its semantics and representation power is indispensable. In this paper, we study the semantics of lparse programs, called the lparse semantics. We show that for a large class of programs, called strongly satisfiable programs, the lparse semantics agrees with the semantics based on conditional satisfaction. However, when the two semantics disagree, a stable model admitted by the lparse semantics may be circularly justified. We then present a transformation, by which an lparse program can be transformed to a strongly satisfiable one, so that no circular models may be generated under the current implementation of smodels. This leads to an investigation of a methodological issue, namely the possibility of compact representation of aggregate programs by lparse programs. We present some experimental results to compare this approach with the ones where aggregates are more explicitly handled.
Using new attribute construction to incorporate the expertise of human experts into a smuggling vessels classification system
Authors: Tsung-Yuan Tseng, Yeou-Ren Shiue, Ke-Chih Ning, Shih-Wei Lin, Wei-Ming Cheng
Venue: Expert Systems with Applications: An International Journal (2009)

Modifying the database originally designed for maritime transportation and harbourside sailing safety management in order to train the data classifier to detect smuggling and illegal immigrant vessels may lead to a lack of class-related attributes, and the accuracy rate of classification may be low. However, some valuable artificial classification rules already exist prior to the building of a data classifier, and it is worth attempting to incorporate them into the database and thus build a more accurate data classifier. With the limiting condition that no extra reference point of the terrain can be added into the system, this research selects the artificial smuggling detection rule ''vessels sail fast towards shore'' deduced by Coast Guard's officers, sets the radar station as the reference point of the shore coordinates, and defines a new attribute, the absolute difference between the anti-course and target azimuth, to demonstrate the ''vessels sail approximately towards radar station or sea'' concept. Matching the original ''speed'' attribute, the newly-modified database includes the intrinsic meaning of ''vessels sail fast towards radar station or sea''. The results show that the accuracy rate of the two data classifiers, the back-propagation neural network (BPN) and support vector machine (SVM), improved by 22% and 14%, respectively. It is significant that incorporation of the expertise of human experts by new attribute construction contributes to the effective learning of the data classifier.
Modern Concepts Applied to C++ - Object Persistence, Reflection, Events, Garbage Collection and Thread Safety in C++
Authors: Torsten Strobl
Venue:  (2007)

C++ is still one of the most powerful programming languages with an amazing list of features. However, many new languages and programming paradigms have arisen, so the choice of the best environment for specific applications becomes more difficult. Therefore, the main question of this book is how to apply capabilities of new concepts to C++. The book covers topics like Object Persistence, Reflection, Value Observation, Event Calling, Garbage Collection and even Thread Safety. For applying these abilities the approach of intelligent data containers, called properties, is picked up. Furthermore, in scope of this book, a template-based C++ Container Library, which implements the mentioned concepts, has been developed. Its name Property Set Library (PSL) is based on the used property approach, and its structure and way of implementation is also described in detail. This book is not only for C++ programmers who are interested in details about usable techniques, the freely available library can also be used practically. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player