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Search engines are continuously employing advanced techniques that aim to capture user intentions and provide results that go beyond the data that simply satisfy the query conditions. Examples include the personalized results, related searches, similarity search, popular and relaxed queries. In this work we introduce a novel query paradigm that considers a(More)
We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty answer set, our framework dynamically computes and suggests alternative queries with less conditions than those the user has initially requested, in order to help the user arrive at a query with a(More)
Log information describing the items the users have selected from the set of answers a query engine returns to their queries constitute an excellent form of indirect user feedback that has been extensively used in the web to improve the effectiveness of search engines. In this work we study how the logs can be exploited to improve the ranking of the results(More)
We present IQR, a system that demonstrates optimization based interactive relaxations for queries that return an empty answer. Given an empty answer, IQR dynamically suggests one relaxation of the original query conditions at a time to the user, based on certain optimization objectives, and the user responds by either accepting or declining the relaxation,(More)
We demonstrate XQ, a query engine that implements a novel technique for searching relevant information on the web and in various data sources, called Exemplar Queries. While the traditional query model expects the user to provide a set of specifications that the elements of interest need to satisfy, XQ expects the user to provide only an element of interest(More)
Keyword query to graph query is a problem which aims at mapping entities and relationships mentioned in a query to entities and relationships in a knowledge-base. It has a very important application in different domains like that of information retrieval, data mining, genomics etc. Obviously keyword queries are preferred by users because they are based on(More)
Information graphs are generic graphs that model different types of information through nodes and edges. Knowledge graphs are the most common type of information graphs in which nodes represent entities and edges represent relationships among them. In this paper, we argue that exploitation of information graphs can lead into novel query answering(More)
Modern search engines employ advanced techniques that go beyond the structures that strictly satisfy the query conditions in an effort to better capture the user intentions. In this work, we introduce a novel query paradigm that considers a user query as an example of the data in which the user is interested. We call these queries exemplar queries. We(More)
We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty-answer set, our framework dynamically computes and suggests alternative queries with fewer conditions than those the user has initially requested, in order to help the user arrive at a query with(More)
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