Mining Tasks from the Web Anchor Text Graph: MSR Notebook Paper for the TREC 2015 Tasks Track
- Paul N. Bennett ,
- Ryen W. White
Proceedings of the 24th Text Retrieval Conference (TREC '15) |
Users may have a variety of tasks that give rise to issuing a particular query. The goal of the Tasks Track at TREC 2015 was to identify all aspects or subtasks of a user’s task as well as the documents relevant to the entire task. This was broken into two parts: (1) Task Understanding which judged relevance of key phrases or queries to the original query (relative to a likely task that would have given rise to both); (2) Task Completion which performed document retrieval and measured usefulness to any task a user with the query might be peforming through either a completion measure that uses both relevance and usefulness criteria or more simply through an ad hoc retrieval measure of relevance alone. We submitted a run in the Task Understanding track. In particular, since the anchor text graph has proven useful in the general realm of query reformulation [2], we sought to quantify the value of extracting key phrases from anchor text in the broader setting of the task understanding track.