CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Algorithms for analysing the temporal structure of discourse
EACL '95 Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics
Inferring discourse relations in context
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
Using temporal profiles of queries for precision prediction
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Web-a-where: geotagging web content
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Automatic TIMEX2 tagging of Korean news
ACM Transactions on Asian Language Information Processing (TALIP) - Special Issue on Temporal Information Processing
Robust temporal processing of news
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
TASIP '01 Proceedings of the workshop on Temporal and spatial information processing - Volume 13
Applying machine learning to Chinese temporal relation resolution
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
On the value of temporal information in information retrieval
ACM SIGIR Forum
Improving search relevance for implicitly temporal queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Temporal processing with the TARSQI toolkit
COLING '08 22nd International Conference on on Computational Linguistics: Demonstration Papers
Use of temporal expressions in web search
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Determining time of queries for re-ranking search results
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Automatic temporal expression normalization with reference time dynamic-choosing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
A comparison of time-aware ranking methods
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
NTLM: a time-enhanced language model based ranking approach for web search
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Answering General Time-Sensitive Queries
IEEE Transactions on Knowledge and Data Engineering
A language modeling approach for temporal information needs
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Extracting focused locations for web pages
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
Hi-index | 12.05 |
Time plays important roles in Web search, because most Web pages contain temporal information and a lot of Web queries are time-related. How to integrate temporal information in Web search engines has been a research focus in recent years. However, traditional search engines have little support in processing temporal-textual Web queries. Aiming at solving this problem, in this paper, we concentrate on the extraction of the focused time for Web pages, which refers to the most appropriate time associated with Web pages, and then we used focused time to improve the search efficiency for time-sensitive queries. In particular, three critical issues are deeply studied in this paper. The first issue is to extract implicit temporal expressions from Web pages. The second one is to determine the focused time among all the extracted temporal information, and the last issue is to integrate focused time into a search engine. For the first issue, we propose a new dynamic approach to resolve the implicit temporal expressions in Web pages. For the second issue, we present a score model to determine the focused time for Web pages. Our score model takes into account both the frequency of temporal information in Web pages and the containment relationship among temporal information. For the third issue, we combine the textual similarity and the temporal similarity between queries and documents in the ranking process. To evaluate the effectiveness and efficiency of the proposed approaches, we build a prototype system called Time-Aware Search Engine (TASE). TASE is able to extract both the explicit and implicit temporal expressions for Web pages, and calculate the relevant score between Web pages and each temporal expression, and re-rank search results based on the temporal-textual relevance between Web pages and queries. Finally, we conduct experiments on real data sets. The results show that our approach has high accuracy in resolving implicit temporal expressions and extracting focused time, and has better ranking effectiveness for time-sensitive Web queries than its competitor algorithms.