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) …

This paper studies conversational approaches to information retrieval, presenting a theory
and model of information interaction in a chat setting. In particular, we consider the question …

Managing the data for Information Retrieval (IR) experiments can be challenging. Dataset
documentation is scattered across the Internet and once one obtains a copy of the data …

Crowdsourcing has become a popular paradigm in data curation, annotation and evaluation
for many artificial intelligence and information retrieval applications. Considerable efforts …

Recommender systems research and practice are fast-develo** topics with growing
adoption in a wide variety of information access scenarios. In this article, we present an …

In order to adopt deep learning for information retrieval, models are needed that can capture
all relevant information required to assess the relevance of a document to a given user …

We integrate irdatasets, ir_measures, and PyTerrier with TIRA in the Information Retrieval
Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and …

In information retrieval, query auto completion (QAC), also known as typeahead [**ao et al.,
2013, Cai et al., 2014b] and auto-complete suggestion [Jain and Mishne, 2010], refers to the …

Ranking in information retrieval has been traditionally approached as a pursuit of relevant
information, under the assumption that the users' information needs are unambiguously …

Neural IR models, such as DRMM and PACRR, have achieved strong results by
successfully capturing relevance matching signals. We argue that the context of these …