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| Content Provider | ACM Digital Library |
|---|---|
| Author | Soboroff, Ian |
| Abstract | Existing methods for measuring the quality of search algorithms use a static collection of documents. A set of queries and a mapping from the queries to the relevant documents allow the experimenter to see how well different search engines or engine configurations retrieve the correct answers. This methodology assumes that the document set and thus the set of relevant documents are unchanging. In this paper, we abandon the static collection requirement. We begin with a recent TREC collection created from a web crawl and analyze how the documents in that collection have changed over time. We determine how decay of the document collection affects TREC systems, and present the results of an experiment using the decayed collection to measure a live web search system. We employ novel measures of search effectiveness that are robust despite incomplete relevance information. Lastly, we propose a methodology of "collection maintenance" which supports measuring search performance both for a single system and between systems run at different points in time. |
| Starting Page | 276 |
| Ending Page | 283 |
| Page Count | 8 |
| File Format | |
| ISBN | 1595933697 |
| DOI | 10.1145/1148170.1148220 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2006-08-06 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Retrieval test collections |
| Content Type | Text |
| Resource Type | Article |
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