Exploring URL Hit Priors for Web Search

@inproceedings{citeulike:593561, abstract = {URL usually contains meaningful information for measuring the relevance of a Web page to a query in Web search. Some existing works utilize URL depth priors (i.e. the probability of being a good page given the length and depth of a URL) for improving some types of Web search tasks. This paper suggests the use of the location of query terms occur in a URL for measuring how well a web page is matched with a user’s information need in web search. First, we define and estimate URL hit types, i.e. the priori probability of being a good answer given the type of query term hits in the URL. The main advantage of URL hit priors (over depth priors) is that it can achieve stable improvement for both informational and navigational queries. Second, an obstacle of exploiting such priors is that shortening and concatenation are frequently used in a URL. Our investigation shows that only 30\% URL hits are recognized by an ordinary word breaking approach. Thus we combine three methods to improve matching. Finally, the priors are integrated into the probabilistic model for enhancing web document retrieval. Our experiments were conducted using 7 query sets of TREC2002, TREC2003 and TREC2004, and show that the proposed approach is stable and improve retrieval effectiveness by 4\%\~{}11\% for navigational queries and 10\% for informational queries.}, address = {London, UK}, author = {Song, Ruihua and Xin, Guomao and Shi, Shuming and Wen, Ji-Rong and Ma, Wei-Ying }, booktitle = {Advances in Information Retrieval: 28th European Conference on IR Research, ECIR 2006}, citeulike-article-id = {593561}, editor = {Lalmas, Mounia and Macfarlane, Andy and R\"{u}ger, Stefan and Tombros, Anastasios and Tsikrika, Theodora and Yavlinsky, Alexei }, keywords = {2get, evaluation, information-retrieval, web}, month = {April}, pages = {277--288}, posted-at = {2006-04-21 13:12:00}, priority = {4}, title = {Exploring URL Hit Priors for Web Search}, year = {2006} }

TY - CONF ID - citeulike:593561 L3 - citeulike-article-id:593561 TI - Exploring URL Hit Priors for Web Search T2 - Advances in Information Retrieval: 28th European Conference on IR Research, ECIR 2006 SP - 277 EP - 288 AD - London, UK N2 - URL usually contains meaningful information for measuring the relevance of a Web page to a query in Web search. Some existing works utilize URL depth priors (i.e. the probability of being a good page given the length and depth of a URL) for improving some types of Web search tasks. This paper suggests the use of the location of query terms occur in a URL for measuring how well a web page is matched with a user’s information need in web search. First, we define and estimate URL hit types, i.e. the priori probability of being a good answer given the type of query term hits in the URL. The main advantage of URL hit priors (over depth priors) is that it can achieve stable improvement for both informational and navigational queries. Second, an obstacle of exploiting such priors is that shortening and concatenation are frequently used in a URL. Our investigation shows that only 30% URL hits are recognized by an ordinary word breaking approach. Thus we combine three methods to improve matching. Finally, the priors are integrated into the probabilistic model for enhancing web document retrieval. Our experiments were conducted using 7 query sets of TREC2002, TREC2003 and TREC2004, and show that the proposed approach is stable and improve retrieval effectiveness by 4%~11% for navigational queries and 10% for informational queries. KW - 2get KW - evaluation KW - information-retrieval KW - web AU - Song, Ruihua AU - Xin, Guomao AU - Shi, Shuming AU - Wen, Ji-Rong AU - Ma, Wei-Ying A2 - Lalmas, Mounia A2 - Macfarlane, Andy A2 - Rüger, Stefan A2 - Tombros, Anastasios A2 - Tsikrika, Theodora A2 - Yavlinsky, Alexei PY - 2006/04// ER -