Results 1 - 10 of 72

Applying Associative Retrieval Techniques to Alleviate the Sparsity Problem in Collaborative Filtering

by Zan Huang, Hsinchun Chen, Daniel Zeng - ACM Transactions on Information Systems , 2004
"... this article, we propose to deal with this sparsity problem by applying an associative retrieval framework and related spreading activation algorithms to explore transitive associations among consumers through their past transactions and feedback. Such transitive associations are a valuable source o ..."
Abstract - Cited by 135 (12 self) - Add to MetaCart
this article, we propose to deal with this sparsity problem by applying an associative retrieval framework and related spreading activation algorithms to explore transitive associations among consumers through their past transactions and feedback. Such transitive associations are a valuable source of information to help infer consumer interests and can be explored to deal with the sparsity problem. To evaluate the effectiveness of our approach, we have conducted an experimental study using a data set from an online bookstore. We experimented with three spreading activation algorithms including a constrained Leaky Capacitor algorithm, a branch-and-bound serial symbolic search algorithm, and a Hopfield net parallel relaxation search algorithm. These algorithms were compared with several collaborative filtering approaches that do not consider the transitive associations: a simple graph search approach, two variations of the user-based approach, and an item-based approach. Our experimental results indicate that spreading activation-based approaches significantly outperformed the other collaborative filtering methods as measured by recommendation precision, recall, the F-measure, and the rank score. We also observed the over-activation effect of the spreading activation approach, that is, incorporating transitive associations with past transactional data that is not sparse may "dilute" the data used to infer user preferences and lead to degradation in recommendation performance

Multi-document summarization by graph search and matching

by Inderjeet Mani - In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-97 , 1997
"... We describe a new method for summarizing similarities and differences in a pair of related documents using a graph representation for text. Concepts denoted by words, phrases, and proper names in the document are represented positionally as nodes in the graph along with edges corresponding to semant ..."
Abstract - Cited by 78 (1 self) - Add to MetaCart
We describe a new method for summarizing similarities and differences in a pair of related documents using a graph representation for text. Concepts denoted by words, phrases, and proper names in the document are represented positionally as nodes in the graph along with edges corresponding to semantic relations between items. Given a perspective in terms of which the pair of documents is to be summarized, the algorithm first uses a spreading activation technique to discover, in each document, nodes semantically related to the topic. The activated graphs of each document are then matched to yield a graph corresponding to similarities and differences between the pair, which is rendered in natural language. An evaluation of these techniques has been carried out.
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A parallel computing approach to creating engineering concept spaces for semantic retrieval: The Illinois Digital Library Initiative project

by Hsinchun Chen, Bruce Schatz, Tobun Ng, Joanne Martinez, Amy Kirchhoff, Chienting Lin, E Computer Society - Ieee Transactions on Pattern Analysis and Machine Intelligence , 1996
"... Abstract-This research presents preliminary results generated from the semantic retrieval research component of the Illinois Digital Library Initiative (DLI) project. Using a variation of the automatic thesaurus generation techniques, to which we refer as the concept space approach, we aimed to crea ..."
Abstract - Cited by 50 (12 self) - Add to MetaCart
Abstract-This research presents preliminary results generated from the semantic retrieval research component of the Illinois Digital Library Initiative (DLI) project. Using a variation of the automatic thesaurus generation techniques, to which we refer as the concept space approach, we aimed to create graphs of domain-specific concepts (terms) and their weighted co-occurrence relationships for all major engineering domains. Merging these concept spaces and providing traversal paths across different concept spaces could potentially help alleviate the vocabulary (difference) problem evident in large-scale information retrieval. We have experimented previously with such a technique for a smaller molecular biology domain (Worm Community System, with IO+ MBs of document collection) with encouraging results. In order to address the scalability issue related to large-scale information retrieval and analysis for the current Illinois DLI project, we recently conducted experiments using the concept space approach on parallel supercomputers. Our test collection included 2+ GBs of computer science and electrical engineering abstracts extracted from the INSPEC database. The concept space approach called for extensive textual and statistical analysis (a form of knowledge discovery) based on automatic indexing and cooccurrence analysis algorithms, both previously tested in the biology domain. Initial testing results using a 512-node CM-5 and a 16processor SGI Power Challenge were promising. Power Challenge was later selected to create a comprehensive computer engineering concept space of about 270,000 terms and 4,000,000+ links using 24.5 hours of CPU time. Our system evaluation involving 12 knowledgeable subjects revealed that the automatically-created computer engineering concept space generated
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A graph-based recommender system for digital library

by Zan Huang, Wingyan Chung, Thian-huat Ong, Hsinchun Chen - In Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries , 2002
"... Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a co ..."
Abstract - Cited by 41 (5 self) - Add to MetaCart
Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, useruser and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.
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Pharos: A Scalable Distributed Architecture for Locating Heterogeneous Information Sources

by R. Dolin, D. Agrawal, L. Dillon, A. El Abbadi - In In Proceedings of the 6th International Conference on Information and Knowledge Management , 1996
"... This paper presents the design of Pharos: a scalable distributed architecture for locating heterogeneous information sources. The system incorporates a hierarchical metadata structure into a multi-level retrieval system. Queries are resolved through an iterative decision-making process. The first st ..."
Abstract - Cited by 38 (7 self) - Add to MetaCart
This paper presents the design of Pharos: a scalable distributed architecture for locating heterogeneous information sources. The system incorporates a hierarchical metadata structure into a multi-level retrieval system. Queries are resolved through an iterative decision-making process. The first step retrieves coarse-grain metadata, about all sources, stored on local, massively replicated, high-level servers. Further steps retrieve more detailed metadata, about a greatly reduced set of sources, stored on remote, sparsely replicated, topic-based mid-level servers. We describe the structure, distribution, and retrieval of the metadata in Pharos to enable users to locate desirable information sources over the Internet. Contents 1 Introduction 1 2 Design Overview 3 2.1 Motivation : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2.2 Example Query : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.3 Multi-Level Approach : : : : : : : : : : :...
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Comparison of Three Vertical Search Spiders

by Michael Chau - IEEE Computer , 2003
"... In domain-specific search experiments, a Web spider based on a neural network algorithm consistently outperformed spiders based on traditional graph search and PageRank algorithms. The Web has plenty of useful resources, but its dynamic, unstructured nature makes them difficult to locate. Search eng ..."
Abstract - Cited by 38 (22 self) - Add to MetaCart
In domain-specific search experiments, a Web spider based on a neural network algorithm consistently outperformed spiders based on traditional graph search and PageRank algorithms. The Web has plenty of useful resources, but its dynamic, unstructured nature makes them difficult to locate. Search engines help, but the number of Web pages now exceeds two billion, making it difficult for generalpurpose engines to maintain comprehensive, up-todate search indexes. Moreover, as the Web grows ever larger, so does information overload in query results. A general-purpose search engine, such as Google (www.google.com) or AltaVista (www. altavista.com), usually generates thousands of hits, many of them irrelevant to the user query. Vertical search engines solve part of the problem by keeping indexes only in specific domains.

A Graph Model for E-Commerce Recommender Systems

by Zan Huang, Wingyan Chung, Hsinchun Chen - Journal of the American Society for Information Science and Technology , 2004
"... this article, we review previous research in recommender systems to identify frequently used approaches and representations. Four recommendation approaches were examined: knowledge engineering, collaborative filtering, a content-based approach, and a hybrid approach. Different recommendation approac ..."
Abstract - Cited by 36 (7 self) - Add to MetaCart
this article, we review previous research in recommender systems to identify frequently used approaches and representations. Four recommendation approaches were examined: knowledge engineering, collaborative filtering, a content-based approach, and a hybrid approach. Different recommendation approaches can be implemented using different analytical methods. Commonly used methods are neighborhood formation, association rule mining, machine learning techniques, etc
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COPLINK Connect: information and knowledge management for law enforcement

by Hsinchun Chen, Jenny Schroeder, Roslin V. Hauck, Linda Ridgeway, Homa Atabakhsh, Harsh Gupta, Chris Boarman, Kevin Rasmussen, Andy W. Clements , 2002
"... Information and knowledge management in a knowledge-intensive and time-critical environment presents a challenge to information technology professionals. In law enforcement, multiple data sources are used, each having different user interfaces. COPLINK Connect addresses these problems by providing o ..."
Abstract - Cited by 34 (5 self) - Add to MetaCart
Information and knowledge management in a knowledge-intensive and time-critical environment presents a challenge to information technology professionals. In law enforcement, multiple data sources are used, each having different user interfaces. COPLINK Connect addresses these problems by providing one easy-to-use interface that integrates different data sources such as incident records, mug shots and gang information, and allows diverse police departments to share data easily. User evaluations of the application allowed us to study the impact of COPLINK on law-enforcement personnel as well as to identify requirements for improving the system. COPLINK Connect is currently being deployed at Tucson Police Department (TPD). D 2002 Elsevier Science B.V. All rights reserved.

Using Coplink to Analyze Criminal-Justice Data

by Roslin Hauck, Roslin V, Harsh Gupta , 1996
"... ial Intelligence Lab with the Tucson Police Department 's law enforcement domain knowledge. Coplink serves the community by bridging the gap between conducting research in cutting-edge technologies and solving real-world problems such as helping police officers fight crime. COPLINK IN TU ..."
Abstract - Cited by 33 (6 self) - Add to MetaCart
ial Intelligence Lab with the Tucson Police Department 's law enforcement domain knowledge. Coplink serves the community by bridging the gap between conducting research in cutting-edge technologies and solving real-world problems such as helping police officers fight crime. COPLINK IN TUCSON The Coplink concept space application, which began as a research project, has evolved into a realtime system being used in everyday police work. The Tucson Police Department had evaluated its information technology and identified several problems that stem from lack of information sharing, integration, and knowledge management. The TPD agreed to participate with UA's Artificial Intelligence Lab in research to investigate the potential of using state-of-the-art, near-term, and cost-effective database, Intranet, and multimedia technologies to make justice information database integration, management, and access more effective. The Coplink project attacks several problems existin

HelpfulMed: Intelligent Searching for Medical Information over the Internet

by Hsinchun Chen, Ann M. Lally, Bin Zhu, Michael Chau - JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY , 2003
"... Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architectur ..."
Abstract - Cited by 28 (18 self) - Add to MetaCart
Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space", and Kohonen-based Self-Organizing Map (SAM) technologies to provide searchers with fine-grained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed allows users to search not only Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results
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