Continuous temporal Top-K query over versioned documents
|Continuous temporal Top-K query over versioned documents|
|Author(s)||Lan C., Zhang Y., Xing C., Li C.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Unknown (Extra: Information management, Decision makers, Support time, Time interval, Time-periods, Top-k query, Weight constraints, Wikipedia, Window-based, Information retrieval)|
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Continuous temporal Top-K query over versioned documents is a 2014 conference paper written in English by Lan C., Zhang Y., Xing C., Li C. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
The management of versioned documents has attracted researchers' attentions in recent years. Based on the observation that decision-makers are often interested in finding the set of objects that have continuous behavior over time, we study the problem of continuous temporal top-k query. With a given a query, continuous temporal top-k search finds the documents that frequently rank in the top-k during a time period and take the weights of different time intervals into account. Existing works regarding querying versioned documents have focused on adding the constraint of time, however lacked to consider the continuous ranking of objects and weights of time intervals. We propose a new interval window-based method to address this problem. Our method can get the continuous temporal top-k results while using interval windows to support time and weight constraints simultaneously. We use data from Wikipedia to evaluate our method.
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