An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
On the design of a learning crawler for topical resource discovery
ACM Transactions on Information Systems (TOIS)
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Information Retrieval
Autonomous Agents and Multi-Agent Systems
Targeted E-commerce Marketing Using Fuzzy Intelligent Agents
IEEE Intelligent Systems
Design and evaluation of a multi-agent collaborative Web mining system
Decision Support Systems - Web retrieval and mining
Assessment of preferences for classification detail in medical information: is uniformity better?
Information Processing and Management: an International Journal
iJADE Web-Miner: An Intelligent Agent Framework for Internet Shopping
IEEE Transactions on Knowledge and Data Engineering
Intelligent Agents on the Web: A Review
Computing in Science and Engineering
Personalized Web Search with Self-Organizing Map
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
The indexable web is more than 11.5 billion pages
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Journal of the American Society for Information Science and Technology
Using HMM to learn user browsing patterns for focused web crawling
Data & Knowledge Engineering - Special issue: WIDM 2004
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
| Hi-index | 0.00 |
The continuing growth of the Internet contents makes difficult the information access, inducing the task of information retrieval highly critical. The search engines often return a huge quantity of Web data, which is irrelevant to the input query. The emergency of personalization in the web search activities demands stable synergies for retrieving relevant information which meets the user needs. This work proposes an agent-based system for supporting customized Web searches. The system replies to a typical web query providing ad-hoc user-profiled links to web pages. the basis of a learning activity, which constitute an initial knowledge The agents collect locally the knowledge during an initial user querying/answering interaction phase and then interpret the meaning of collected information, by exploiting ontologies: they discover new semantic correlations among query terms, in order to refine the description of queries. These queries are used in the web search to provide more relevant replies, which reflect the user preferences and interest. This proposal represents a valid support for evidence-based applications, where sensitive contexts such as health care, medicine require high quality and unambiguous information in the specialized lexical domain.