کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
515805 867098 2016 26 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
GTE-Rank: A time-aware search engine to answer time-sensitive queries
ترجمه فارسی عنوان
رتبه GTE: موتور جستجوی آگاه به زمان برای پاسخ به سؤالات حساس به زمان
کلمات کلیدی
بازیابی اطلاعات زمانی؛ نمایش حساس به زمان؛ زمانی رتبه بندی مجدد؛ درک جستجوهای زمانی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• We propose a novel temporal re-ranking algorithm.
• We devise and provide new datasets for time-sensitive evaluation purposes.
• We conduct comparative experiments (including algorithms with a temporal focus).
• We investigate the effectiveness of GRank by running a crowdsourcing experiment.
• We build a prototype system that can be tested by the research community.

In the web environment, most of the queries issued by users are implicit by nature. Inferring the different temporal intents of this type of query enhances the overall temporal part of the web search results. Previous works tackling this problem usually focused on news queries, where the retrieval of the most recent results related to the query are usually sufficient to meet the user's information needs. However, few works have studied the importance of time in queries such as “Philip Seymour Hoffman” where the results may require no recency at all. In this work, we focus on this type of queries named “time-sensitive queries” where the results are preferably from a diversified time span, not necessarily the most recent one. Unlike related work, we follow a content-based approach to identify the most important time periods of the query and integrate time into a re-ranking model to boost the retrieval of documents whose contents match the query time period. For that purpose, we define a linear combination of topical and temporal scores, which reflects the relevance of any web document both in the topical and temporal dimensions, thus contributing to improve the effectiveness of the ranked results across different types of queries. Our approach relies on a novel temporal similarity measure that is capable of determining the most important dates for a query, while filtering out the non-relevant ones. Through extensive experimental evaluation over web corpora, we show that our model offers promising results compared to baseline approaches. As a result of our investigation, we publicly provide a set of web services and a web search interface so that the system can be graphically explored by the research community.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing & Management - Volume 52, Issue 2, March 2016, Pages 273–298
نویسندگان
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