Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
TINTIN: a system for retrieval in text tables
DL '97 Proceedings of the second ACM international conference on Digital libraries
A machine learning based approach for table detection on the web
Proceedings of the 11th international conference on World Wide Web
Modern Information Retrieval
Automatic extraction of table metadata from digital documents
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
ChemXSeer: a digital library and data repository for chemical kinetics
Proceedings of the ACM first workshop on CyberInfrastructure: information management in eScience
Enabling Interactive Access to Web Tables
Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends
Enhancing browsing experience of table and image elements in web pages
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Enabling efficient browsing and manipulation of web tables on smartphone
HCII'11 Proceedings of the 14th international conference on Human-computer interaction: towards mobile and intelligent interaction environments - Volume Part III
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Tables are ubiquitous. Unfortunately, no search engine supportstable search. In this paper, we propose a novel table specificsearching engine, TableSeer, to facilitate the table extracting, indexing, searching, and sharing. In addition, wepropose an extensive set of medium-independent metadata to precisely present tables. Given a query, TableSeer ranks the returned results using an innovative ranking algorithm - TableRank with a tailored vector space model and a novel term weightingscheme. Experimental results show that TableSeer outperforms existing search engines on table search. In addition, incorporating multiple weighting factors can significantly improve the ranking results.