Automated learning of decision rules for text categorization
ACM Transactions on Information Systems (TOIS)
A comparison of classifiers and document representations for the routing problem
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Context-sensitive learning methods for text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Dynamic reference sifting: a case study in the homepage domain
Selected papers from the sixth international conference on World Wide Web
Learning to extract symbolic knowledge from the World Wide Web
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Question Answering from Frequently Asked Question Files: Experiences with the FAQ Finder System
Question Answering from Frequently Asked Question Files: Experiences with the FAQ Finder System
Personal ontologies for web navigation
Proceedings of the ninth international conference on Information and knowledge management
Goal-Oriented Information Retrieval Using Feedback from Users
WAIM '01 Proceedings of the Second International Conference on Advances in Web-Age Information Management
Categorizing web search results into meaningful and stable categories using fast-feature techniques
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Proceedings of the 2008 ACM symposium on Applied computing
PathRank: Web Page Retrieval with Navigation Path
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Looking Ahead: A Comparison of Page Preview Techniques for Goal-Directed Web Navigation
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
Searching documents based on relevance and type
ECIR'07 Proceedings of the 29th European conference on IR research
A path-based approach for web page retrieval
World Wide Web
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This paper proposes a novel approach to accurately searching Web pages for relevant information in problem solving by specifying a Web document category instead of the user's task. Accessing information from World Wide Web pages as an approach to problem solving has become commonplace. However, such a search is difficult with current search services, since these services only provide keyword-based search methods that are equivalent to narrowing down the target references according to domains. However, problem solving usually involves both a domain and a task. Accordingly, our approach is based on problem solving tasks. To specify a user's problem solving task, we introduce the concept of document types that directly relate to the problem solving tasks; with this approach, users can easily designate problem solving tasks. We implemented PageTypeSearch system based on our approach. Classifier of PageTypeSearch classifies Web pages into the document types by comparing their pages with typical structural characteristics of the types. We compare PageTypeSearch using the document typeindices with a conventional keyword-based search system in experiments. The average precision of the document type-based search is 88.9%, while the average precision of the keyword-based search is 31.2%. Moreover, the number of irrelevant references gathered by our system is about one-thirteenth that of traditional keyword-based search systems. Our approach has practical advantages for problem solving by introducing the viewpoint of tasks to achieve higher performance.