Carlos Castro-herrera, Chuan Duan, Jane Clel, Bamshad Mobasher
Requirements related problems, especially those originating from inadequacies in the human-intensive task of eliciting stakeholders ’ needs and desires, have contributed to many failed and...
Using Data Mining and Recommender Systems to Scale up the Requirements Process (2009)
Jane Cleland-huang, Bamshad Mobasher
Ultra-Large-Scale (ULS) software systems ’ projects are anticipated to be highly complex and to involve thousands, or even hundreds of thousands of stakeholders. Unfortunately numerous accounts of...
Exploring the Impact of Profile Injection Attacks in Social Tagging Systems ⋆ (2009)
Maryam Ramezani, Runa Bhaumik, Tom Schimoler, Robin Burke, Bamshad Mobasher
Abstract. As in the case of all open and adaptive systems that rely on user input to organize and present content, social tagging systems are vulnerable to spamming and profile injection attacks....
Chuan Duan, Jane Clel, Bamshad Mobasher
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human analyst to perform...
Personalization in Folksonomies Based on Tag Clustering (2009)
Jonathan Gemmell, Andriy Shepitsen, Bamshad Mobasher, Robin Burke
Collaborative tagging systems, sometimes referred to as “folksonomies, ” enable Internet users to annotate or search for resources using custom labels instead of being restricted by pre-defined...
Personalized Recommendation in Social Tagging Systems Using Hierarchical Clustering (2009)
Andriy Shepitsen, Jonathan Gemmell, Bamshad Mobasher, Robin Burke
Collaborative tagging applications allow Internet users to annotate resources with personalized tags. The complex network created by many annotations, often called a folksonomy, permits users the...
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms ∗ (2009)
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-based collaborative...
Abstract Secure Personalization: Building Trustworthy Recommender Systems ∗ (2009)
Recent research has tried to quantify the vulnerabilities of collaborative recommender systems in the face of profile injection attacks (also known as shilling attacks) and to devise more secure...
Eui-Hong (Sam) Han George Karypis Vipin Kumar (2009)
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
ABSTRACT Classification Features for Attack Detection in Collaborative Recommender Systems ∗ (2009)
Robin Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in recommendations that...
Profile Injection Attack Detection for Securing Collaborative Recommender Systems 1 (2009)
Chad Williams, Bamshad Mobasher
Researchers have shown that collaborative recommender systems, the most common type of web personalization system, are highly vulnerable to attack. Attackers can use automated means to inject a large...
Chad A. Williams, Bamshad Mobasher
Abstract Collaborative recommender systems are known to be highly vulnerable to profile injection attacks, attacks that involve the insertion of biased profiles into the ratings database for the...
Robin Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik
Collaborative recommender systems are highly vulnerable to attack. Attackers can use automated means to inject a large number of biased profiles into such a system, resulting in recommendations that...
Abstract Representing User Information Context with Ontologies (2008)
Ahu Sieg, Bamshad Mobasher, Robin Burke, Ganesh Prabu, Steve Lytinen
One of the key factors for accurate and effective information access is the user context. The critical elements that make up a user's information context include the semantic knowledge about the...
Evaluation of Profile Injection Attacks In Collaborative Recommender Systems (2008)
Chad Williams, Runa Bhaumik, Jj S, Bamshad Mobasher, Robin Burke
Significant vulnerabilities have been identified in collaborative recommender systems. The open nature of collaborative filtering allows attackers to inject biased profile data and force the system...
Eui-hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher, Mining Charu, C. Aggarwal, ...
The Bulletin of the Technical Committee on Data Engineering is published quarterly and is distributed to all TC members. Its scope includes the design, implementation, modelling, theory and...
16:25–16:50 WebRelievo: A System for Browsing and Analyzing the (2008)
Mark Levene, Ra Poulovassilis, Judit Bar-ilan, Mark Levene, Mazlita Mat-hassan, Yen-yu Chen, ...
14:50–15:15 Modeling Semantic Web Services with OPM/S A Human and Machine-Interpretable Language
Ontological User Profiles as the Context Model in Web Search (2008)
Ahu Sieg, Bamshad Mobasher, Robin Burke
One of the key factors for effective personalization of information access is the user context. Our proposed approach for representing the user context involves implicitly building ontological user...
Using Probabilistic Latent Semantic Analysis to Identify Web User Segments (2008)
Xin Jin, Yanzan Kevin Zhou, Bamshad Mobasher
Web usage mining techniques are often used to identify user access patterns. However, to understand the factors that lead to common navigational patterns, it is necessary to develop techniques that...
Learning Ontology-Based User Profiles: A Semantic Approach to Personalized Web Search (2008)
Ahu Sieg, Bamshad Mobasher, Robin Burke
Abstract—Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user...
2 Profile Injection Attacks (2008)
! Vulnerabilities in collaborative recommendation " Types of attacks and examples " Background and summary of previous work " Basic attack models " Effectiveness...
Learning Ontology-Based User Profiles: A Semantic Approach to Personalized Web Search (2008)
Ahu Sieg, Bamshad Mobasher, Robin Burke
Abstract—Every user has a distinct background and a specific goal when searching for information on the Web. The goal of Web search personalization is to tailor search results to a particular user...
WebKDD 2005 – Web Mining and Web Usage Analysis Post-Workshop report (2008)
Olfa Nasraoui, Osmar R. Zaïane, Myra Spiliopoulou, Tg E, Bamshad Mobasher, Brij Masand, ...
In this report, we summarize the contents and outcomes of
Philip Chan, Ronaldo Menezes, Debasis Mitra, Eraldo Ribeiro, Marius Silaghi, Ahu Sieg, ...
Knowledge Discovery in Multiple Databases................................................Ramesh K. Rayudu 42
Bettina Berendt, Andreas Hotho, Ernestina Menasalvas, Bamshad Mobasher, Myra Spiliopoulou, Gerd Stumme, ...
3 Agenda
B.: A framework for the analysis of attacks against social tagging systems. In (2008)
Runa Bhaumik, Maryam Ramezani, Robin Burke, Bamshad Mobasher
Social tagging systems provide an open platform for users to share and annotate their resources such as photos and URLs. Due to their open nature, however, these systems present a security problem....
WebACE: A Web Agent for Document Categorization and Exploration (2007)
George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore
We propose an agent for exploring and categorizing documents on the World Wide Web. The heart of the agent is an automatic categorization of a set of documents, combined with a process for generating...
Multi-Agent Negotiation using Combinatorial Auctions with Precedence Constraints* (2007)
John Collinsrand, Maria Gini, Bamshad Mobasher
We present a system for multi-agent contract negotiation, implemented as an auctionbased market architecture called MAGNET. A principal feature of MAGNET is support for negotiation of contracts based...
Improving the E ectiveness of Collaborative Filtering on Anonymous Web Usage Data (2007)
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa
Recommender systems based on collaborative ltering usually require real-time comparison of users ' ratings on objects. In the context of Web personalization, particularly at the early stages of...
Mixed-Initiative Decision Support in Agent-Based (2007)
Automated Contracting John, John Collins, Corey Bilot, Maria Gini, Bamshad Mobasher
Using principles from Expected Utility Theory,we analyze the criteria that a customer agent in agent-based automated contracting would use in making decisions during the bidding cycle. We use the...
Plan Execution by Contracting in a Multi-Agent Environment (2007)
John Collins Corey, John Collins, Corey Bilot, Maxsim Tsvetovat, Maria Gini, Bamshad Mobasher
We present a computational model of planning, scheduling, and execution that is capable of supporting the interactions of a self-interested agent with other agents in a contracting environment over...
Representing context in web search with ontological user profiles (2007)
Ahu Sieg, Bamshad Mobasher, Robin Burke
Abstract. One of the key factors for effective personalization of information access is the user context. We propose a framework which integrates several critical elements that make up the user...
Ontological user profiles for personalized web search (2007)
Ahu Sieg, Bamshad Mobasher, Robin Burke
The goal of Web search personalization is to tailor search results to a particular user based on that user’s interests and preferences, thus allowing for more efficient information access. One of...
Ontological user profiles for personalized web search (2007)
Ahu Sieg, Bamshad Mobasher, Robin Burke
The goal of Web search personalization is to tailor search results to a particular user based on that user’s interests and preferences, thus allowing for more efficient information access. One of...
Analysis and detection of segment-focused attacks against collaborative recommendation (2006)
Bamshad Mobasher, Robin Burke, Chad Williams, Runa Bhaumik
Abstract. Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. These vulnerabilities mostly emanate from the open nature of such systems and their...
Detection of obfuscated attacks in collaborative recommender systems (2006)
Chad Williams, Bamshad Mobasher, Robin Burke, Jeff S, Runa Bhaumik
Abstract. The vulnerability of collaborative recommender systems has been well established; particularly to reverse-engineered attacks designed to bias the system in an attacker’s favor. Recent...
Detecting profile injection attacks in collaborative recommender systems (2006)
Robin Burke, Bamshad Mobasher, Chad Williams, Runa Bhaumik
Collaborative recommender systems are known to be highly vulnerable to profile injection attacks, attacks that involve the insertion of biased profiles into the ratings database for the purpose of...
Effective attack models for shilling item-based collaborative filtering systems (2005)
Bamshad Mobasher, Robin Burke, Runa Bhaumik, Chad Williams
Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. These vulnerabilities mostly emanate from the open nature of such systems and their reliance...
Collaborative recommendation vulnerability to focused bias injection attacks (2005)
Robin Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams
Significant vulnerabilities have recently been identified in collaborative recommender systems. Attackers who cannot be readily distinguished from ordinary users may inject biased data in an attempt...
Segment-based injection attacks against collaborative filtering recommender systems (2005)
Robin Burke, Bamshad Mobasher, Runa Bhaumik, Chad Williams
Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. Researchers have shown that attackers can manipulate a system’s recommendations by...
Limited knowledge shilling attacks in collaborative filtering systems (2005)
Robin Burke, Bamshad Mobasher, Runa Bhaumik
Recent research in recommender systems has shown that collaborative filtering algorithms are highly susceptible to attacks that insert biased profile data. Theoretical analyses and empirical...
Y.: A Web Recommendation System Based on Maximum Entropy (2005)
Xin Jin, Bamshad Mobasher, Yanzan Zhou
We propose a Web recommendation system based on a maximum entropy model. Under the maximum entropy principle, we can combine multiple levels of knowledge about users ’ navigational behavior in...
Photo Dr, Stefano Lonardi, Olfa Nasraoui, Osmar R. Zaïane, Myra Spiliopoulou, Bamshad Mobasher, ...
In Conjunction with
Using concept hierarchies to enhance user queries in web-based information retrieval (2004)
Ahu Sieg, Bamshad Mobasher, Steve Lytinen, Robin Burke
The effectiveness of Internet search engines is often hampered by the ambiguity of user queries and the reluctance or inability of users to build less ambiguous multi-word queries. Our system, ARCH,...
R.: Inferring user’s information context from user profiles and concept hierarchies (2004)
Ahu Sieg, Bamshad Mobasher, Robin Burke
Abstract The critical elements that make up a user’s information context include the user profiles that reveal long-term interests and trends, the short-term information need as might be expressed...
Chairs York Sure, Andreas Hotho, Andreas Hotho, Lise Getoor, Lise Getoor, Bamshad Mobasher
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine on-line opinions from the Internet and...
Using concept hierarchies to enhance user queries in web-based information retrieval (2004)
Ahu Sieg, Bamshad Mobasher, Steve Lytinen, Robin Burke
The effectiveness of Internet search engines is often hampered by the ambiguity of user queries and the reluctance or inability of users to build less ambiguous multi-word queries. Neither simple...
John Collins, Wolfgang Ketter, Maria Gini, Bamshad Mobasher
We are interested in supporting multi-agent contracting, in which customer agents solicit the resources and capabilities of other, self-interested agents in order to accomplish their goals. Goals may...
Multi-agent negotiation using combinatorial auctions with precedence constraints (2002)
John Collins, Maria Gini, Bamshad Mobasher
We present a system for multi-agent contract negotiation, implemented as an auctionbased market architecture called MAGNET. A principal feature of MAGNET is support for negotiation of contracts based...
Discovery and evaluation of aggregate usage profiles for web personalization (2002)
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa
Abstract: Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these techniques,...
Using Ontologies to Discover Domain-Level Web Usage Profiles (2002)
Honghua (Katy) Dai, Bamshad Mobasher
Usage patterns discovered through Web usage mining are effective in capturing item-to-item and user-to-user relationships and similarities at the level of user sessions Without the benefit of deeper...
Privacy Concerns Research Issues and Future Directions (2002)
Bettina Berendt, Bettina Berendt, Bamshad Mobasher, Myra Spiliopoulou, Bamshad Mobasher, Myra Spiliopoulou
1 3 4
Data Acquisition and Data Preparation Evaluation of Web Site Success (2002)
Bettina Berendt, Bamshad Mobasher, Myra Spiliopoulou, Bettina Berendt, Bamshad Mobasher, Myra Spiliopoulou
Multi-agent negotiation using combinatorial auctions with precedence constraints (2002)
John Collins, Maria Gini, Bamshad Mobasher
We present a system for multi-agent contract negotiation, implemented as an auctionbased market architecture called MAGNET. A principal feature of MAGNET is support for negotiation of contracts based...
Improving the effectiveness of Collaborative Filtering on Anonymous Web Usage Data (2001)
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakagawa
Recommender systems based on collaborative filtering usually require real-time comparison of users ’ ratings on objects. In the context of Web personalization,particularly at the early stages of a...
An adaptive agent for web exploration based of concept hierarchies (2001)
Scott Parent, Bamshad Mobasher, Steve Lytinen
In this paper we present the design of a client-side agent, named ARCH, for assisting users in one of the most difficult information retrieval tasks, i.e., that of formulating an effective search...
Integrating Web usage and content mining for more e ective personalization (2000)
Bamshad Mobasher, Hoghua Dai, Tao Luo, Yuqing Sun, Jiang Zhu
Abstract. Recent proposals have suggested Web usage mining as an enabling mechanism to overcome the problems associated with more traditional Web personalization techniques such as collaborative or...
Data preparation for mining world wide web browsing patterns (1999)
Robert Cooley, Bamshad Mobasher, Jaideep Srivastava
Abstract. The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. The complexity of tasks such as Web site...
Partitioning-based clustering for web document categorization. Decision Support Systems (1999)
Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
Clustering techniques have been used by manyintelligent software agents in order to retrieve, lter, and categorize documents available on the World Wide Web. Clustering is also useful in extracting...
Founding President of the Engineering Graduate (1999)
Existing approaches to Web personalization often rely heavily on explicit and subjective user input resulting in static profiles which are prone to biases. In this paper we present a usagebased Web...
Data preparation for mining world wide web browsing patterns (1999)
Robert Cooley, Bamshad Mobasher, Jaideep Srivastava
Abstract. The World Wide Web (WWW) continues to grow at an astounding rate in both the sheer volume of traffic and the size and complexity of Web sites. The complexity of tasks such as Web site...
Partitioning-Based Clustering for Web Document Categorization (1999)
Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Partitioning-Based Clustering for Web Document Categorization (1999)
Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Partitioning-Based Clustering for Web Document Categorization (1999)
Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)
Daniel Boley, Maria Gini, Robert Gross, Eui-Hong (Sam) Han, Kyle Hastings, George Karypis, ...
We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...
Partitioning-Based Clustering for Web Document Categorization (1999)
Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)
Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...
Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)
Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...
WebACE: A Web Agent for Document Categorization and Exploration (1998)
Eui-Hong Han, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...
We propose an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an automatic categorization of a set of documents, combined with...
Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results (1998)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher
Clustering of data in a large dimension space is of a great interest in many data mining applications. In this paper, we propose a method for clustering of data in a high dimensional space based on a...
WebACE: A Web Agent for Document Categorization and Exploration (1998)
Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
We propose an agent for exploring and categorizing documents on the World Wide Web based on a user pro#le. The heart of the agent is an automatic categorization of a set of documents, combined with a...
Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results (1998)
Eui-Hong Sam, Bamshad Mobasher
Clustering of data in a large dimension space is of a great interest in many data mining applications. In this paper, we propose a method for clustering of data in a high dimensional space based on a...
Jerome Moore, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Jerome Moore, Eui-Hong Han, Daniel Boley, Maria Gini, Robert Gross, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
Temporal Strategies in a Multi-Agent Contracting Protocol (1997)
John Collins, Scott Jamison, Maria Gini, Bamshad Mobasher
Much recent work in automated contracting in multi-agent environments has focused on the design and analysis of protocols that encourage customers and suppliers to negotiate fairly, and that attempt...
A Market Architecture for Multi-Agent Contracting (1997)
John Collins, Scott Jamison, Bamshad Mobasher, Maria Gini
We present a generalized market architecture that provides support for a variety of types of transactions, from simple buying and selling of goods and services to complex multi-agent contract...
Eui-Hong (Sam) Han George Karypis Vipin Kumar Bamshad Mobasher (1997)
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
Clustering In A High-Dimensional Space Using Hypergraph Models (1997)
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
Clustering In A High-Dimensional Space Using Hypergraph Models (1997)
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
Jerome Moore, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...
Clustering techniques have been used by manyintelligent software agents in order to retrieve, #lter, and categorize documents available on the World Wide Web. Clustering is also useful in extracting...
Jerome Moore, Eui-Hong (Sam) Han, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...
Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...
MAGMA: An Agent-Based Virtual Market for Electronic Commerce (1997)
Maksim Tsvetovatyy, Maria Gini, Bamshad Mobasher, Zbigniew Wieckowski
In this paper, we propose an architecture for an agent-based virtual market that includes all elements required for simulating a real market. These elements include a communication infrastructure,...
Web Mining: Pattern Discovery from World Wide Web Transactions (1996)
Bamshad Mobasher, Namit Jain, Eui-Hong (Sam) Han, Jaideep Srivastava
Web-based organizations often generate and collect large volumes of data in their daily operations. Analyzing such data can help these organizations to determine the life time value of clients,...
Web Mining: Pattern discovery from World Wide Web transactions (1996)
Bamshad Mobasher, Namit Jain, Jaideep Srivastava
Web-based organizations often generate and collect large volumes of data in their daily operations. Analyzing such data can help these organizations to determine the life time value of clients,...
Generalized knowledge-based semantics for multi-valued logic programs /--by Bamshad Mobasher. (1994)
Typescript (photocopy)
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
Clustering In A High-Dimensional Space Using Hypergraph Models (1987)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher
Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...
Automatic personalization based on Web usage mining (0000)
The article focuses on cognitive modeling for games and animation The article deals with the issue of automatic personalization based on web usage mining. Most personalization systems...
Automatic personalization based on Web usage mining
The article focuses on cognitive modeling for games and animation The article deals with the issue of automatic personalization based on web usage mining. Most personalization systems...
Clustering Based On Association Rule Hypergraphs
Eui-Hong (Sam) Han, George Karypis, Bamshad Mobasher
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These discovered clusters...
Clustering Based On Association Rule Hypergraphs
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These discovered clusters...
WebACE: A Web Agent for Document Categorization and Exploration
Eui-Hong Sam, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...
We propose an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an automatic categorization of a set of documents, combined with...