- 2018年3月30日 15:10 - 16:10
- 早稲田大学 西早稲田キャンパス 63-05-06
Getting rid of the ten blue links
- Professor Mark Sanderson (RMIT University)
In this talk, I will first give a brief overview of the IR group at RMIT. Then I will describe the work we are doing at RMIT to change one of the commonest web pages we all look at: the Search Result Page (SERP). In our work we are looking to replace the SERP with a set of answer passages that address the user’s query. In the context of general web search, the problem of finding answer passages has not been explored extensively. Previous studies have found that many informational queries can be answered by a passage of text extracted from a retrieved document, relieving the user from having to read the actual document. While current passage retrieval methods that focus on topical relevance have been shown to be not effective at finding answers, the result shows that more knowledge is required to identify answers in the document.
We have been formulating the answer passage extraction problem as a summarization task. We initially used term distributions extracted from a Community Question Answering (CQA) service to generate more effective summaries of retrieved web pages. An experiment was conducted to see the benefit of using the CQA data in finding answer passages. We analyze the fraction of answers covering a set of queries, the quality of the corresponding result from the answering service, and their impact on the generated summaries. I will also talk about recent work where we re-rank retrieved passages according to the summary quality and incorporating document summarizability into the ranking function.
Mark Sanderson is a Professor at the School of Computer Science and Information Technology, RMIT University, Melbourne. He received B.Sc. (hons) and Ph.D. degrees in computer science from the University of Glasgow, Glasgow, U.K., in 1988 and 1997, respectively. Mark is an Associate Editor of ACM Transactions on the Web; and co-editor of Foundations and Trends in Information Retrieval.