Query Expansion Methods are proposed to solve many problems of information retrieval systems, but most of these methods do not use the information of interactions between the users and the system. In our approach, we applied a Query Recommendation Algorithm on a list of past user queries, to extract the most associated queries to the input query, and used it in a Probabilistic Query Expansion m...

-----------------------------------------------------------------------ABSTRACT---------------------------------------------------------In this paper we suggest a method that, given a query presented to a search engine, proposes a list of concerned queries. The concerned queries are founded in antecedently published queries, and can be published by the user to the search engine to tune or redir...

A recent query-log mining approach for query recommendation is based on Query Flow Graphs, a markov-chain representation of the query reformulation process followed by users of Web Search Engines trying to satisfy their information needs. In this paper we aim at extending this model by providing methods for dealing with evolving data. In fact, users’ interests change over time, and the knowledg...

Searching for relevant code in the local code base is a common activity during software maintenance. However, previous research indicates that 88% of manually-composed search queries retrieve no relevant results. One reason that many searches fail is existing search tools’ dependence on string matching algorithms, which cannot find semantically-related code. To solve this problem by helping dev...

In this paper we propose a method that, given a query submitted to a search engine, suggests a list of related queries. The related queries are based in previously issued queries, and can be issued by the user to the search engine to tune or redirect the search process. The method proposed is based on a query clustering process in which groups of semantically similar queries are identified. The...

In recent years, there has been an increasing effort to develop techniques for related entity recommendation, where the task is to retrieve a ranked list of related entities given a keyword query. Another trend in the area of information retrieval (IR) is to take temporal aspects of a given query into account when assessing the relevance of documents. However, while this has become an establish...

In this paper, we address a critical problem in conversation systems: limited input interpretation capabilities. When an interpretation error occurs, users often get stuck and cannot recover due to a lack of guidance from the system. To solve this problem, we present a hybrid natural language query recommendation framework that combines natural language generation with query retrieval. When rec...

Tools for visual data exploration allow users to visually browse through and analyze datasets to possibly reveal interesting information hidden in the data that users are a priori unaware of. Such tools rely on both query recommendations to select data to be visualized and visualization recommendations for these data to best support users in their visual data exploration process. EVLIN (explori...

Access plan recommendation is a query optimization approach that executes new queries using prior created execution plans (QEPs). The optimizer divides the space into clusters in mentioned method. However, traditional clustering algorithms take significant amount of time for such large datasets. MapReduce distributed computing model provides efficient solutions storing and processing vast quant...