Impact of document representation on neural ad hoc retrieval

Document Type

Conference Proceeding

Source of Publication

International Conference on Information and Knowledge Management, Proceedings

Publication Date

10-17-2018

Abstract

© 2018 Association for Computing Machinery. Neural embeddings have been effectively integrated into information retrieval tasks including ad hoc retrieval. One of the benefits of neural embeddings is they allow for the calculation of the similarity between queries and documents through vector similarity calculation methods. While such methods have been effective for document matching, they have an inherent bias towards documents that are sized relatively similarly. Therefore, the difference between the query and document lengths, referred to as the query-document size imbalance problem, becomes an issue when incorporating neural embeddings and their associated similarity calculation models into the ad hoc document retrieval process. In this paper, we propose that document representation methods need to be used to address the size imbalance problem and empirically show their impact on the performance of neural embedding-based ad hoc retrieval. In addition, we explore several types of document representation methods and investigate their impact on the retrieval process. We conduct our experiments on three widely used standard corpora, namely Clueweb09B, Clueweb12B and Robust04 and their associated topics. Summarily, we find that document representation methods are able to effectively address the query-document size imbalance problem and significantly improve the performance of neural ad hoc retrieval. In addition, we find that a document representation method based on a simple term-frequency shows significantly better performance compared to more sophisticated representation methods such as neural composition and aspect-based methods.

ISBN

9781450360142

Publisher

Association for Computing Machinery

First Page

1635

Last Page

1638

Disciplines

Computer Sciences

Keywords

Calculations, Knowledge management, Associated topics, Document matching, Document Representation, Document Retrieval, Imbalance problem, Representation method, Retrieval process, Similarity calculation, Information retrieval

Scopus ID

85058034898

Indexed in Scopus

yes

Open Access

no

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