Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Abstract. In this paper, we target document ranking in a highly technical field with the aim to approximate a ranking that is obtained through an existing ontology (knowledge stru...
Eric SanJuan, Fidelia Ibekwe-Sanjuan, Juan Manuel ...
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
Keyword search is widely recognized as a convenient way to retrieve information from XML data. In order to precisely meet users' search concerns, we study how to effectively r...
Zhifeng Bao, Jiaheng Lu, Tok Wang Ling, Liang Xu, ...
Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given sour...