With the ever increasing size of the web, relevant information extraction on the Internet with
a query formed by a few keywords has become a big challenge. Query Expansion (QE) …

The relative ineffectiveness of information retrieval systems is largely caused by the
inaccuracy with which a query formed by a few keywords models the actual user information …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

Beginning with a conceptual approach to the representation of space adopted by GIS, this
book examines spatial databases, the acquisition and compilation of data, the analytical …

Statistical language models have recently been successfully applied to many information
retrieval problems. A great deal of recent work has shown that statistical language models …

Query logs record the queries and the actions of the users of search engines, and as such
they contain valuable information about the interests, the preferences, and the behavior of …

Current search engines do not, in general, perform well with longer, more verbose queries.
One of the main issues in processing these queries is identifying the key concepts that will …

Semantic Similarity relates to computing the similarity between conceptually similar but not
necessarily lexically similar terms. Typically, semantic similarity is computed by map** …

In this paper, we investigate the use of recurrent neural networks (RNNs) in the context of
search-based online advertising. We use RNNs to map both queries and ads to real valued …

Query expansion, in the form of pseudo-relevance feedback or relevance feedback, is a
common technique used to improve retrieval effectiveness. Most previous approaches have …