Does More Context Help? Effects of Context Window and Application Source on Retrieval Performance

Author:

Vuong Tung1ORCID,Andolina Salvatore2,Jacucci Giulio1,Ruotsalo Tuukka3

Affiliation:

1. University of Helsinki, Helsinki, Finland

2. University of Palermo and University of Helsinki, Helsinki, Finland

3. University of Helsinki and University of Copenhagen, Copenhagen, Denmark

Abstract

We study the effect of contextual information obtained from a user’s digital trace on Web search performance. Contextual information is modeled using Dirichlet–Hawkes processes (DHP) and used in augmenting Web search queries. The context is captured by monitoring all naturally occurring user behavior using continuous 24/7 recordings of the screen and associating the context with the queries issued by the users. We report a field study in which 13 participants installed a screen recording and digital activity monitoring system on their laptops for 14 days, resulting in data on all Web search queries and the associated context data. A query augmentation (QAug) model was built to expand the original query with semantically related terms. The effects of context window and source were determined by training context models with temporally varying context windows and varying application sources. The context models were then utilized to re-rank the QAug model. We evaluate the context models by using the Web document rankings of the original query as a control condition compared against various experimental conditions: (1) a search context condition in which the context was sourced from search history; (2) a non-search context condition in which the context was sourced from all interactions excluding search history; (3) a comprehensive context condition in which the context was sourced from both search and non-search histories; and (4) an application-specific condition in which the context was sourced from interaction histories captured on a specific application type. Our results indicated that incorporating more contextual information significantly improved Web search rankings as measured by the positions of the documents on which users clicked in the search result pages. The effects and importance of different context windows and application sources, along with different query types are analyzed, and their impact on Web search performance is discussed.

Funder

COADAPT

PON AIM

Academy of Finland

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,General Business, Management and Accounting,Information Systems

Reference74 articles.

1. Mixtures of dirichlet processes with applications to bayesian nonparametric problems;Antoniak Charles E.;Annals of Statistics,1974

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