Learning to Merge Search Results for Efficient Distributed Information Retrieval
نویسندگان
چکیده
Merging search results from different servers is a major problem in Distributed Information Retrieval. We used Regression-SVM and Ranking-SVM which would learn a function that merges results based on information that is readily available: i.e. the ranks, titles, summaries and URLs contained in the results pages. By not downloading additional information, such as the full document, we decrease bandwidth usage. CORI and Round Robin merging were used as our baselines; surprisingly, our results show that the SVMmethods do not improve over those baselines.
منابع مشابه
Review of ranked-based and unranked-based metrics for determining the effectiveness of search engines
Purpose: Traditionally, there have many metrics for evaluating the search engine, nevertheless various researchers’ proposed new metrics in recent years. Aware of this new metrics is essential to conduct research on evaluation of the search engine field. So, the purpose of this study was to provide an analysis of important and new metrics for evaluating the search engines. Methodology: This is ...
متن کاملAn Effective Path-aware Approach for Keyword Search over Data Graphs
Abstract—Keyword Search is known as a user-friendly alternative for structured languages to retrieve information from graph-structured data. Efficient retrieving of relevant answers to a keyword query and effective ranking of these answers according to their relevance are two main challenges in the keyword search over graph-structured data. In this paper, a novel scoring function is proposed, w...
متن کاملدیداری کردن نتایج جستوجو در فرایند بازیابی اطلاعات
Purpose: One of the most effective ways to achieve optimum information retrieval is through visualization of Information. Search strategies, probing skills, querying of information needs and analysis of information play a significant role in the accessing of necessary and useful information. Besides the factors mentioned above, information visualization can increase the availability level of in...
متن کاملContext-based Information seeking behavior among students of Kharazmi University
Background and Aim: The present study has been done in order to survey contextualized information retrieval behavior by the students of Kharazmi University. Methods: This is descriptive applied research. Statistical population includes all the students currently studying at the Kharazmi University in the time of research. Sample of research includes 196 students selected by convenience sampling...
متن کاملAdaptive and Efficient Image Retrieval with One-Class Support Vector Machines for Inter-Query Learning
We present an extension of previous work on improving the initial image retrieval set by exploiting both intra and inter-query learning. In most Content-Based Image Retrieval (CBIR) systems based on Relevance Feedback (RF), all prior experience is lost whenever a user generates a new query, thus inter-query information is not used. In previous work, a system was developed that learns One-class ...
متن کامل