Information Systems (TOIS)


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ACM Transactions on Information Systems (TOIS), Volume 34 Issue 4, September 2016

Query Performance Prediction Using Reference Lists
Anna Shtok, Oren Kurland, David Carmel
Article No.: 19
DOI: 10.1145/2926790

The task of query performance prediction is to estimate the effectiveness of search performed in response to a query when no relevance judgments are available. We present a novel probabilistic analysis of the performance prediction task. The...

Comparing Pointwise and Listwise Objective Functions for Random-Forest-Based Learning-to-Rank
Muhammad Ibrahim, Mark Carman
Article No.: 20
DOI: 10.1145/2866571

Current random-forest (RF)-based learning-to-rank (LtR) algorithms use a classification or regression framework to solve the ranking problem in a pointwise manner. The success of this simple yet effective approach coupled with the inherent...

Probabilistic Models for Contextual Agreement in Preferences
Loc Do, Hady W. Lauw
Article No.: 21
DOI: 10.1145/2854147

The long-tail theory for consumer demand implies the need for more accurate personalization technologies to target items to the users who most desire them. A key tenet of personalization is the capacity to model user preferences. Most of the...

TopPRF: A Probabilistic Framework for Integrating Topic Space into Pseudo Relevance Feedback
Jun Miao, Jimmy Xiangji Huang, Jiashu Zhao
Article No.: 22
DOI: 10.1145/2956234

Traditional pseudo relevance feedback (PRF) models choose top k feedback documents for query expansion and treat those documents equally. When k is determined, feedback terms are selected without considering the reliability of these...

Examining Additivity and Weak Baselines
Sadegh Kharazmi, Falk Scholer, David Vallet, Mark Sanderson
Article No.: 23
DOI: 10.1145/2882782

We present a study of which baseline to use when testing a new retrieval technique. In contrast to past work, we show that measuring a statistically significant improvement over a weak baseline is not a good predictor of whether a similar...

Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation
Xiangfeng Luo, Junyu Xuan, Jie Lu, Guangquan Zhang
Article No.: 24
DOI: 10.1145/2903719

The evolution potential estimation of news events can support the decision making of both corporations and governments. For example, a corporation could manage its public relations crisis in a timely manner if a negative news event about this...

Diversifying Query Auto-Completion
Fei Cai, Ridho Reinanda, Maarten De Rijke
Article No.: 25
DOI: 10.1145/2910579

Query auto-completion assists web search users in formulating queries with a few keystrokes, helping them to avoid spelling mistakes and to produce clear query expressions, and so on. Previous work on query auto-completion mainly centers around...