NDLI: Improving searcher models using mouse cursor activity

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Salton award lecture: information retrieval as engineering science

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Explanatory semantic relatedness and explicit spatialization for exploratory search

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Automatic refinement of patent queries using concept importance predictors

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Generating reformulation trees for complex queries

Social-network analysis using topic models

A generalized hidden Markov model with discriminative training for query spelling correction

Online result cache invalidation for real-time web search

Exploring social influence for recommendation: a generative model approach

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Category hierarchy maintenance: a data-driven approach

Reactive index replication for distributed search engines

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Rhetorical relations for information retrieval

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Crowdsourcing for search evaluation and social-algorithmic search

User evaluation of query quality

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Group matrix factorization for scalable topic modeling

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Aspect-based opinion mining from product reviews

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Creating temporally dynamic web search snippets

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RDF Xpress: a flexible expressive RDF search engine

Detecting candidate named entities in search queries

Query performance prediction for IR

Sketch-based image similarity search with a pen and paper interface

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Task-aware search assistant

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TweetSpector: entity-based retrieval of tweets

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Efficient estimation of aspect weights

Multi-platform image search using tag enrichment

Emotion tagging for comments of online news by meta classification with heterogeneous information sources

Estimating the magic barrier of recommender systems: a user study

Explaining neighborhood-based recommendations

Exploiting term dependence while handling negation in medical search

Exploring example-based person search in email

Exploring tag relevance for image tag re-ranking

Fast on-line learning for multilingual categorization

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Genre classification for million song dataset using confidence-based classifiers combination

GLASE 0.1: eyes tell more than mice

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Identifying entity aspects in microblog posts

Impact of assessor disagreement on ranking performance

Incorporating statistical topic information in relevance feedback

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Investigating performance predictors using monte carlo simulation and score distribution models

Learning to select a time-aware retrieval model

Learning-based time-sensitive re-ranking for web search

Lightweight contrastive summarization for news comment mining

Looking inside the box: context-sensitive translation for cross-language information retrieval

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New assessment criteria for query suggestion

On automatically tagging web documents from examples

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On judgments obtained from a commercial search engine

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On real-time ad-hoc retrieval evaluation

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Optimizing parameters of the expected reciprocal rank

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Parallelizing ListNet training using spark

Predicting lifespans of popular tweets in microblog

Preliminary study of technical terminology for the retrieval of scientific book metadata records

Queries without clicks: evaluating retrieval effectiveness based on user feedback

Retrieval evaluation on focused tasks

Rewarding term location information to enhance probabilistic information retrieval

Scheduling queries across replicas

Re-examining search result snippet examination time for relevance estimation

Sentiment identification by incorporating syntax, semantics and context information

Short text classification using very few words

Summarizing the differences from microblogs

Survival analysis of click logs

Text selections as implicit relevance feedback

Time to judge relevance as an indicator of assessor error

Towards alias detection without string similarity: an active learning based approach

Towards zero-click mobile IR evaluation: knowing what and knowing when

Twanchor text: a preliminary study of the value of tweets as anchor text

Unsupervised linear score normalization revisited

User-aware caching and prefetching query results in web search engines

Using eye-tracking with dynamic areas of interest for analyzing interactive information retrieval

Using PageRank to infer user preferences

Utilizing inter-document similarities in federated search

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\$100,000 prize jackpot. call now!: identifying the pertinent features of SMS spam

Improving searcher models using mouse cursor activity

Content Provider	ACM Digital Library
Author	White, Ryen W. Buscher, Georg Huang, Jeff Wang, Kuansan
Abstract	Web search components such as ranking and query suggestions analyze the user data provided in query and click logs. While this data is easy to collect and provides information about user behavior, it omits user interactions with the search engine that do not hit the server; these logs omit search data such as users' cursor movements. Just as clicks provide signals for relevance in search results, cursor hovering and scrolling can be additional implicit signals. In this work, we demonstrate a technique to extend models of the user's search result examination state to infer document relevance. We start by exploring recorded user interactions with the search results, both qualitatively and quantitatively. We find that cursor hovering and scrolling are signals telling us which search results were examined, and we use these interactions to reveal latent variables in searcher models to more accurately compute document attractiveness and satisfaction. Accuracy is evaluated by computing how well our model using these parameters can predict future clicks for a particular query. We are able to improve the click predictions compared to a basic searcher model for higher ranked search results using the additional log data.
Starting Page	195
Ending Page	204
Page Count	10
File Format	PDF
ISBN	9781450314725
DOI	10.1145/2348283.2348313
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-08-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Searcher models Search result examination Click data User interactions Scrolling Cursor data
Content Type	Text
Resource Type	Article

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