Information filtering via fuzzy hierarchical induction
10 Oct 2004-Vol. 4, pp 3576-3581
TL;DR: An adaptive algorithm is proposed in this work for teaming the user profile based on his initial profile and on queries' interpretation using fuzzy concept hierarchies, and the preliminary results are promising.
Abstract: An adaptive algorithm is proposed in this work for teaming the user profile based on his initial profile and on queries' interpretation using fuzzy concept hierarchies. The dynamics of the user profile is modeled by employing a new concept, time-words vector hyperspace. The preliminary results from applying this new approach are promising. Future plans and recommendations for further expanding are provided.
Citations
More filters
01 Jan 2006
TL;DR: A Probabilistic, Logic-Based Framework for Automated Web Directory Alignment and Automatic Thematic Categorization of Multimedia Documents using Ontological Information and Fuzzy Algebra are presented.
Abstract: Probability in Ontologies and Semantic Web.- BayesOWL: Uncertainty Modeling in Semantic Web Ontologies.- Modeling Uncertainty in Semantic Web Taxonomies.- A Probabilistic, Logic-Based Framework for Automated Web Directory Alignment.- The SP Theory and the Representation and Processing of Knowledge.- Fuzzy Logic in Ontologies and Semantic Web.- Dynamic Services for Open Ambient Intelligence Systems.- Development of Ontologies by the Lowest Common Abstraction of Terms Using Fuzzy Hypernym Chains.- Beyond the Semantic Web: Fuzzy Logic-Based Web Intelligence.- An Ontology-Based Method for User Model Acquisition.- On Some Problems of Decision-Making Under Uncertainty in the Semantic Web.- Automatic Thematic Categorization of Multimedia Documents using Ontological Information and Fuzzy Algebra.
41 citations
01 Jan 2006
2 citations
Cites background from "Information filtering via fuzzy hie..."
...Some of our work on fuzzy hierarchies of concepts can be found in [ 17-20 ]....
[...]
References
More filters
Book•
01 Jan 1983
TL;DR: Reading is a need and a hobby at once and this condition is the on that will make you feel that you must read.
Abstract: Some people may be laughing when looking at you reading in your spare time. Some may be admired of you. And some may want be like you who have reading hobby. What about your own feel? Have you felt right? Reading is a need and a hobby at once. This condition is the on that will make you feel that you must read. If you know are looking for the book enPDFd introduction to modern information retrieval as the choice of reading, you can find here.
12,059 citations
"Information filtering via fuzzy hie..." refers background in this paper
...1 WordNet is an on-line lexical reference system available at: http://www.cogsci.princeton.edu/cgi-bin/webwn1.7.1 Keywords: Information filtering, fuzzy induction, user profile....
[...]
01 May 1998
TL;DR: z Searching enhancement y Parallel search, searching keywords refinement, relevant feedback z Browsing assistant y Learning, Recommending, Alias, Monitoring bookmarks, More like, Sending page to friends, Prefetching hiperlinks z Offline browsing y downloading following pages, getting references and printing it out.
Abstract: z Searching enhancement y Parallel search, searching keywords refinement, relevant feedback z Browsing assistant y Learning, Recommending, Alias, Monitoring bookmarks, More like, Sending page to friends, Prefetching hiperlinks z Offline browsing y downloading following pages, getting references and printing it out z Filtering HTTP header, cookie, block animation to speed up z Checking html page : error finding, dead links, z Dynamically setting up : search engines, dictionary z Programming in java WebMate architecture
577 citations
01 Jul 1993
TL;DR: The IS-A links define a generalization/specialization hierarchy that is not sufficient to reliably select the correct sense of a noun from the set of fine sense distinctions in WordNet; and missing correct matches because of incorrect sense resolution has a much more deleterious effect on retrieval performance than does making spurious matches.
Abstract: This paper describes an automatic indexing procedure that uses the “IS-A” relations contained within WordNet and the set of nouns contained in a text to select a sense for each plysemous noun in the text. The result of the indexing procedure is a vector in which some of the terms represent word senses instead of word stems. Retrieval experiments comparing the effectivenss of these sense-based vectors vs. stem-based vectors show the stem-based vectors to be superior overall, although the sense-based vectors do improve the performance of some queries. The overall degradation is due in large part to the difficulty of disambiguating senses in short query statements. An analysis of these results suggests two conclusions: the IS-A links define a generalization/specialization hierarchy that is not sufficient to reliably select the correct sense of a noun from the set of fine sense distinctions in WordNet; and missing correct matches because of incorrect sense resolution has a much more deleterious effect on retrieval performance than does making spurious matches.
538 citations
08 Feb 1997
TL;DR: The Fab system strikes a balance between these two approaches, taking advantage of the shared interests among users without losing the benefits of the representations provided by content analysis.
Abstract: An adaptive recommendation service seeks to adapt to its users, providing increasingly personalized recommendations over time. In this paper we introduce the "Fab" adaptive web page recommendation service. There has been much research on analyzing document content in order to improve recommendations or search results. More recently researchers have begun to explore how the similarities between users can be exploited to the same ends. The Fab system strikes a balance between these two approaches, taking advantage of the shared interests among users without losing the benefits of the representations provided by content analysis. Running since March 1996, it has been populated with a collection of agents for the collection and selection of web pages, whose interaction fosters emergent collaborative properties. In this paper we explain the design of the system architecture and report the results of our first experiment, evaluating recommendations provided to a group of test users.
279 citations
"Information filtering via fuzzy hie..." refers methods in this paper
...The coordinates of the documents and queries vectors are calculated using the traditional TF-IDF technique....
[...]
Dissertation•
01 Jan 1994
TL;DR: Experimental results indicate that Newt can be personalized to serve some of the news ltering needs of the user, in particular, those that are more regular and predictable, and the basic framework for personalized information ltering agents is presented.
Abstract: A personalized information ltering system must specialize to current interests of the user and adapt as they change over time. It must also explore newer domains for potentially interesting information. A learning approach to building personalized information ltering systems is proposed. The system is designed as a collection of information ltering interface agents. Interface Agents are intelligent and autonomous computer programs which learn users' preferences and act on their behalf | electronic personal assistants that automate tasks for the user. This thesis presents the basic framework for personalized information ltering agents, and describes an implementation, \Newt", built using the framework. Newt uses a keyword based ltering algorithm. The learning mechanisms used are relevance feedback and the genetic algorithm. The user interface is friendly and accessible to both naive as well as power users. Experimental results indicate that Newt can be personalized to serve some of the news ltering needs of the user, in particular, those that are more regular and predictable. Relevance feedback is good for specializing to user interests. The genetic algorithm causes the system to adapt and explore for new types of information. This demonstrates that Interface Agents are a promising approach to the problem of designing personalized information ltering. Abstract A personalized information ltering system must specialize to current interests of the user and adapt as they change over time. It must also explore newer domains for potentially interesting information. A learning approach to building personalized information ltering systems is proposed. The system is designed as a collection of information ltering interface agents. Interface Agents are intelligent and autonomous computer programs which learn users' preferences and act on their behalf | electronic personal assistants that automate tasks for the user. This thesis presents the basic framework for personalized information ltering agents, and describes an implementation, \Newt", built using the framework. Newt uses a keyword based ltering algorithm. The learning mechanisms used are relevance feedback and the genetic algorithm. The user interface is friendly and accessible to both naive as well as power users. Experimental results indicate that Newt can be personalized to serve some of the news ltering needs of the user, in particular, those that are more regular and predictable. Relevance feedback is good for specializing to user interests. The genetic algorithm causes the system to adapt and explore for new types of information. This demonstrates that Interface Agents are a promising approach to the problem …
229 citations
"Information filtering via fuzzy hie..." refers methods in this paper
...Hypernyms extracted by WordNet1 and fuzzy concept hierarchies are used in order to find the user’s categories of interest....
[...]