This work investigates personalized social search based on the user's social relations--
search results are re-ranked according to their relations with individuals in the user's social …

Personalization of information retrieval (PIR) is aimed at tailoring a search toward individual
users and user groups by taking account of additional information about users besides their …

The query-flow graph [Boldi et al., CIKM 2008] is an aggregated representation of the latent
querying behavior contained in a query log. Intuitively, in the query-flow graph a directed …

The ability to aggregate huge volumes of queries over a large population of users allows
search engines to build precise models for a variety of query-assistance features such as …

Dual-encoder-based dense retrieval models have become the standard in IR. They employ
large Transformer-based language models, which are notoriously inefficient in terms of …

Social tagging systems have gained increasing popularity as a method of annotating and
categorizing a wide range of different web resources. Web search that utilizes social tagging …

Addressing user's information needs has been one of the main goals of Web search engines
since their early days. In some cases, users cannot see their needs immediately answered …

Neural document ranking approaches, specifically transformer models, have achieved
impressive gains in ranking performance. However, query processing using such over …

Defining a measure of similarity between queries is an interesting and difficult problem. A
reliable query-similarity measure can be used in a variety of applications such as query …

The web has largely become a very social environment and will continue to become even
more so. People are not only enjoying their social visibility on the Web but also increasingly …