ABSTRACT
Web search is probably the single most important application on the Internet. The most famous search techniques are perhaps the PageRank and HITS algorithms. These algorithms are motivated by the observation that a hyperlink from a page to another is an implicit conveyance of authority to the target page. They exploit this social phenomenon to identify quality pages, e.g., "authority" pages and "hub" pages. In this paper we argue that these algorithms miss an important dimension of the Web, the temporal dimension. The Web is not a static environment. It changes constantly. Quality pages in the past may not be quality pages now or in the future. These techniques favor older pages because these pages have many in-links accumulated over time. New pages, which may be of high quality, have few or no in-links and are left behind. Bringing new and quality pages to users is important because most users want the latest information. Research publication search has exactly the same problem. This paper studies the temporal dimension of search in the context of research publication search. We propose a number of methods deal with the problem. Our experimental results show that these methods are highly effective.
- A. Arasu, J. Cho, H. Garcia-Molina, A. Paepcke, and S. Raghavan. Searching the Web. ACM Transactions on Internet Technology, 1(1), 2001. Google ScholarDigital Library
- S. Brin, L. Page. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30, 1998. Google ScholarDigital Library
- A. Borodin, J. S. Rosenthal, G. O. Roberts, and P. Tsaparas, Finding authorities and hubs from link structures on the world wide web. WWW-2001. Google ScholarDigital Library
- S. Chakrabarti, B. Dom, D. Gibson, J. Kleinberg, P. Raghavan, and S. Rajagopalan. Automatic resource compilation by analyzing hyperlink structure and associated text. WWW-1998. Google ScholarDigital Library
- T. Haveliwala. Topic-sensitive PageRank. WWW-2002. Google ScholarDigital Library
- J. Kleinberg. Authoritative sources in a hyperlinked environment. ACM-SIAM Symposium on Discrete Algorithms, 1998. Google ScholarDigital Library
- J. Kleinberg, S. R. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. The Web as a graph: measurements, models, and methods. International Conference on Combinatorics and Computing, 1999. Google ScholarDigital Library
- S. Lawrence, K. Bollacker, and C. L. Giles. Indexing and retrieval of scientific literature. CIKM-99. Google ScholarDigital Library
Index Terms
- On the temporal dimension of search
Recommendations
Improving Ranking Consistency for Web Search by Leveraging a Knowledge Base and Search Logs
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge ManagementIn this paper, we propose a new idea called ranking consistency in web search. Relevance ranking is one of the biggest problems in creating an effective web search system. Given some queries with similar search intents, conventional approaches typically ...
Identifying popular search goals behind search queries to improve web search ranking
AIRS'11: Proceedings of the 7th Asia conference on Information Retrieval TechnologyWeb users usually have a certain search goal before they submit a search query. However, many laypersons can't transform their search goals into suitable queries. Thus, understanding original search goals behind a query is very important for search ...
Reducing Click and Skip Errors in Search Result Ranking
WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data MiningSearch engines provide result summaries to help users quickly identify whether or not it is worthwhile to click on a result and read in detail. However, users may visit non-relevant results and/or skip relevant ones. These actions are usually harmful to ...
Comments