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However, these approaches do not accomplish the end goal of a search system\u2014that of retrieving a set of potentially relevant documents for the evolving information need during a search session. This article takes the problem of query prediction one step further by investigating the problem of contextual recommendation within a search session. More specifically, given the partial context information of a session in the form of a small number of queries, we investigate how a search system can effectively predict the documents that a user would have been presented with had he continued the search session by submitting subsequent queries. To address the problem, we propose a model of contextual recommendation that seeks to capture the underlying semantics of information need transitions of a current user\u2019s search context. This model leverages information from a number of past interactions of other users with similar interactions from an existing search log. To identify similar interactions, as a novel contribution, we propose an embedding approach that jointly learns representations of both individual query terms and also those of queries (in their entirety) from a search log data by leveraging session-level containment relationships. Our experiments conducted on a large query log, namely the AOL, demonstrate that using a joint embedding of queries and their terms within our proposed framework of document retrieval outperforms a number of text-only and sequence modeling based baselines.<\/jats:p>","DOI":"10.1145\/3488667","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T21:53:46Z","timestamp":1637186026000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts"],"prefix":"10.1145","volume":"40","author":[{"given":"Procheta","family":"Sen","sequence":"first","affiliation":[{"name":"Dublin City University, Ireland"}]},{"given":"Debasis","family":"Ganguly","sequence":"additional","affiliation":[{"name":"University of Glasgow, Dublin, United Kingdom"}]},{"given":"Gareth J. 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