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• 901 creator jing-he.
• 901 creator xiaoming-li.
• 901 type InProceedings.
• 901 label "Advanced Evaluation of Web Search - Methodology and Technology".
• 901 sameAs 901.
• 901 abstract "It is no doubt that search is critical to the web. And I believe it will be of similar importance to the semantic web. Once you are talking about searching from billions of objects, it will be impossible to always give a single right result, no matter how intelligent the search engine is. Instead, a set of possible results will be provided for the user to choose from. Moreover, if we consider the trade-off between the system costs of generating a single right result and a set of possible results, we may choose the latter. This will naturally lead to the question of how to decide on and present the set to the user and how to evaluate the outcome. In this presentation, I will talk about some new results in the methodology and technology developed for evaluation of web search technologies and systems. As we know, the dominant method for evaluating search engines is the Cranfield paradigm, which employs a test collection to qualify the systems' performance. However, the modern search engines are much different than the traditional information retrieval systems when the Cranfield paradigm was proposed: 1. Mostmodernsearchengineshavemuchmorefeatures,suchasquery-dependent document snippets and query suggestions, and the quality of such features can affect the users' effectiveness to find out useful information; 2. The document collections used in search engines are much larger than ever, so the complete test collection that contain all query-document judgments is not available. As response to the above differences and difficulties, the evaluation based on implicit feedback is a promising alternative methodology employed in IR evaluation. With this approach, no extra human effort is required to judge the querydocument relevance. Instead, such judgments information can be automatically predicted from real users' implicit feedback data. There are three key issues in this methodology: 1. How to predict the query-document relevance and other useful features that useful to qualify the search engine performance; 2. If the complete "judgments" are not available, how can we efficiently collect the most critical information that can determine the system performance; 3. Because more than query-document relevance features can affect the performance, how can they integrate to be a good metric to predict the system performance. We will show a set of technologies dealing with these issues. While semantic web search may present different requirements from web search, evaluation of any search technology will be inevitable. As such, I hope the materials covered in the talk will benefit some of you in semantic web community in the future.".
• 901 hasAuthorList authorList.
• 901 isPartOf proceedings.
• 901 keyword "semantic web".
• 901 title "Advanced Evaluation of Web Search - Methodology and Technology".