TY - GEN
T1 - Reasoning about knowledge from the web (extended abstract)
AU - Kasneci, Gjergji
PY - 2012
Y1 - 2012
N2 - In the presence of a vast amount of user generated content evolving around entities such as people, locations, products, events, etc., it seems that documentoriented retrieval is rather old-fashioned. Imagine an HIV-relevant search task that with the goal of finding drugs that may interfere with HIV protease inhibitors. Retrieving an exhaustive list of explicit results (i.e., drugs that may interfere with HIV protease inhibitors) can be crucial for people suffering from HIV, whose health depends on the unmediated effect of protease inhibitors. Moreover it might be desirable to have the drugs in the result list ranked by their probability of interfering with protease inhibitors. In order to automatically retrieve such an exhaustive list of ranked answers, there are two subtasks that have to be addressed: (1) knowledge about drugs that stand in an interference relationship to protease inhibitors needs to be extracted from various web pages and appropriately combined, (2) the drugs need to be ranked by their probability of interfering with protease inhibitors. Neither of these tasks can be addressed by state-of-the-art search engines. Expecting the user to manually inspect retrieved documents to construct an exhaustive list of answers is simply unrealistic. As a matter of fact, major players in the search engine industry have recognized these issues and are attempting to shift the focus towards knowledge retrieval. For example, in 2010, Google acquired Metaweb, the company behind Freebase, one of the largest knowledge bases with explicit facts about real-world entities. In 2011, Google's search group was restructured and renamed into "knowledge group" [6]. Another example is Microsoft's Bing, which has undergone similar changes in recent years. By the end of 2009 Bing was returning Wolfram Alpha results to entity-related and scholarly queries [8], and by the end 2010 Bing announced the new "health search experience" with the focus "on further enabling people to get relevant information and make better decisions" [7].
AB - In the presence of a vast amount of user generated content evolving around entities such as people, locations, products, events, etc., it seems that documentoriented retrieval is rather old-fashioned. Imagine an HIV-relevant search task that with the goal of finding drugs that may interfere with HIV protease inhibitors. Retrieving an exhaustive list of explicit results (i.e., drugs that may interfere with HIV protease inhibitors) can be crucial for people suffering from HIV, whose health depends on the unmediated effect of protease inhibitors. Moreover it might be desirable to have the drugs in the result list ranked by their probability of interfering with protease inhibitors. In order to automatically retrieve such an exhaustive list of ranked answers, there are two subtasks that have to be addressed: (1) knowledge about drugs that stand in an interference relationship to protease inhibitors needs to be extracted from various web pages and appropriately combined, (2) the drugs need to be ranked by their probability of interfering with protease inhibitors. Neither of these tasks can be addressed by state-of-the-art search engines. Expecting the user to manually inspect retrieved documents to construct an exhaustive list of answers is simply unrealistic. As a matter of fact, major players in the search engine industry have recognized these issues and are attempting to shift the focus towards knowledge retrieval. For example, in 2010, Google acquired Metaweb, the company behind Freebase, one of the largest knowledge bases with explicit facts about real-world entities. In 2011, Google's search group was restructured and renamed into "knowledge group" [6]. Another example is Microsoft's Bing, which has undergone similar changes in recent years. By the end of 2009 Bing was returning Wolfram Alpha results to entity-related and scholarly queries [8], and by the end 2010 Bing announced the new "health search experience" with the focus "on further enabling people to get relevant information and make better decisions" [7].
UR - http://www.scopus.com/inward/record.url?scp=84870916487&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-35623-0_19
DO - 10.1007/978-3-642-35623-0_19
M3 - Conference contribution
AN - SCOPUS:84870916487
SN - 9783642356223
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 186
EP - 188
BT - Current Trends in Web Engineering - ICWE 2012 International Workshops, MDWE, ComposableWeb, WeRE, QWE, and Doctoral Consortium, Revised Selected Papers
T2 - 12th ICWE 2012, Co-located with 8th International Workshop on MDWE 2012, 4th International Workshop on Lightweight Integration on the Web, ComposableWeb 2012, 3rd Workshop on WeRE 2012, 3rd International Workshop on QWE 2012, and Doctoral Consortium
Y2 - 23 July 2012 through 27 July 2012
ER -