NDLI: Context- and Content-aware Embeddings for Query Rewriting in Sponsored Search

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Salton Award Lecture: People, Interacting with Information

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Retrieval of Relevant Opinion Sentences for New Products

Learning to Extract Local Events from the Web

Optimised Scheduling of Online Experiments

Inferring Searcher Attention by Jointly Modeling User Interactions and Content Salience

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Learning to Reweight Terms with Distributed Representations

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Splitting Water: Precision and Anti-Precision to Reduce Pool Bias

Learning by Example: Training Users with High-quality Query Suggestions

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Uncovering Crowdsourced Manipulation of Online Reviews

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Personalized Recommendation via Parameter-Free Contextual Bandits

BROOF: Exploiting Out-of-Bag Errors, Boosting and Random Forests for Effective Automated Classification

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Parametric and Non-parametric User-aware Sentiment Topic Models

GeoSoCa: Exploiting Geographical, Social and Categorical Correlations for Point-of-Interest Recommendations

Sequential Testing for Early Stopping of Online Experiments

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Non-Compositional Term Dependence for Information Retrieval

User Variability and IR System Evaluation

In Situ Insights

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An Introduction to Click Models for Web Search: SIGIR 2015 Tutorial

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CricketLinking: Linking Event Mentions from Cricket Match Reports to Ball Entities in Commentaries

Controversy Detection and Stance Analysis

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Bringing Order to the Job Market: Efficient Job Offer Categorization in E-Recruitment

IR Evaluation: Modeling User Behavior for Measuring Effectiveness

SIGIR 2015 Workshop on Temporal, Social and Spatially-aware Information Access (#TAIA2015)

Time-Aware Authorship Attribution for Short Text Streams

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NeuroIR 2015: Neuro-Physiological Methods in IR Research

A Priori Relevance Based On Quality and Diversity Of Social Signals

ERICA: Expert Guidance in Validating Crowd Answers

Transfer Learning for Information Retrieval

Location in Search

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SPS'15: 2015 International Workshop on Social Personalization & Search

Document Comprehensiveness and User Preferences in Novelty Search Tasks

Large-scale Image Retrieval using Neural Net Descriptors

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Challenges and Opportunities in Online Evaluation of Search Engines

IR Evaluation: Designing an End-to-End Offline Evaluation Pipeline

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Cost-Aware Result Caching for Meta-Search Engines

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From Unlabelled Tweets to Twitter-specific Opinion Words

SciNet: Interactive Intent Modeling for Information Discovery

Spoken Conversational Search: Information Retrieval over a Speech-only Communication Channel

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Load-sensitive CPU Power Management for Web Search Engines

Online News Tracking for Ad-Hoc Queries

Retrieval from Noisy E-Discovery Corpus in the Absence of Training Data

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Opinion Spammer Detection in Web Forum

Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review

Time Pressure and System Delays in Information Search

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Sign-Aware Periodicity Metrics of User Engagement for Online Search Quality Evaluation

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Modeling Website Topic Cohesion at Scale to Improve Webpage Classification

Topic-centric Classification of Twitter User's Political Orientation

Word Embedding based Generalized Language Model for Information Retrieval

A Head-Weighted Gap-Sensitive Correlation Coefficient

On Term Selection Techniques for Patent Prior Art Search

Automatic Feature Generation on Heterogeneous Graph for Music Recommendation

Differences in Eye-Tracking Measures Between Visits and Revisits to Relevant and Irrelevant Web Pages

Reducing Hubness: A Cause of Vulnerability in Recommender Systems

Modularity-Based Query Clustering for Identifying Users Sharing a Common Condition

Understanding Temporal Query Intent

On the Reusability of Open Test Collections

Towards Vandalism Detection in Knowledge Bases: Corpus Construction and Analysis

About the 'Compromised Information Need' and Optimal Interaction as Quality Measure for Search Interfaces

I See You: Person-of-Interest Search in Social Networks

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Features of Disagreement Between Retrieval Effectiveness Measures

Subsequence Search in Event-Interval Sequences

Searcher in a Strange Land: Understanding Web Search from Familiar and Unfamiliar Locations

Evaluating Retrieval Models through Histogram Analysis

Inter-Category Variation in Location Search

Reachability based Ranking in Interactive Image Retrieval

Modeling Multi-query Retrieval Tasks Using Density Matrix Transformation

Predicting User Behavior in Display Advertising via Dynamic Collective Matrix Factorization

Zero-shot Image Tagging by Hierarchical Semantic Embedding

Using Term Location Information to Enhance Probabilistic Information Retrieval

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Exploiting User and Business Attributes for Personalized Business Recommendation

Speeding up Document Ranking with Rank-based Features

Mining Measured Information from Text

An Initial Investigation into Fixed and Adaptive Stopping Strategies

Regularised Cross-Modal Hashing

Adapted B-CUBED Metrics to Unbalanced Datasets

A Time-aware Random Walk Model for Finding Important Documents in Web Archives

A Test Collection for Spoken Gujarati Queries

Discovering Experts across Multiple Domains

Using Key Concepts in a Translation Model for Retrieval

On the Cost of Phrase-Based Ranking

Location-Aware Model for News Events in Social Media

Exploring Opportunities to Facilitate Serendipity in Search

Combining Orthogonal Information in Large-Scale Cross-Language Information Retrieval

Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty

Challenges of Mathematical Information Retrievalin the NTCIR-11 Math Wikipedia Task

Probabilistic Multileave for Online Retrieval Evaluation

Twitter Sentiment Analysis with Deep Convolutional Neural Networks

Anchoring and Adjustment in Relevance Estimation

Cognitive Activity during Web Search

Personalized Semantic Ranking for Collaborative Recommendation

Active Learning for Entity Filtering in Microblog Streams

Relevance-aware Filtering of Tuples Sorted by an Attribute Value via Direct Optimization of Search Quality Metrics

Multi-source Information Fusion for Personalized Restaurant Recommendation

Joint Matrix Factorization and Manifold-Ranking for Topic-Focused Multi-Document Summarization

Towards Understanding the Impact of Length in Web Search Result Summaries over a Speech-only Communication Channel

Early Detection of Topical Expertise in Community Question Answering

LBMCH: Learning Bridging Mapping for Cross-modal Hashing

Gibberish, Assistant, or Master?: Using Tweets Linking to News for Extractive Single-Document Summarization

Context-aware Point-of-Interest Recommendation Using Tensor Factorization with Social Regularization

Adaptive User Engagement Evaluation via Multi-task Learning

Compact Snippet Caching for Flash-based Search Engines

When Personalization Meets Conformity: Collective Similarity based Multi-Domain Recommendation

Sub-document Timestamping of Web Documents

Context- and Content-aware Embeddings for Query Rewriting in Sponsored Search

Content Provider	ACM Digital Library
Author	Silvestri, Fabrizio Grbovic, Mihajlo Djuric, Nemanja Radosavljevic, Vladan Bhamidipati, Narayan
Abstract	Search engines represent one of the most popular web services, visited by more than 85% of internet users on a daily basis. Advertisers are interested in making use of this vast business potential, as very clear intent signal communicated through the issued query allows effective targeting of users. This idea is embodied in a sponsored search model, where each advertiser maintains a list of keywords they deem indicative of increased user response rate with regards to their business. According to this targeting model, when a query is issued all advertisers with a matching keyword are entered into an auction according to the amount they bid for the query, and the winner gets to show their ad. One of the main challenges is the fact that a query may not match many keywords, resulting in lower auction value, lower ad quality, and lost revenue for advertisers and publishers. Possible solution is to expand a query into a set of related queries and use them to increase the number of matched ads, called query rewriting. To this end, we propose rewriting method based on a novel query embedding algorithm, which jointly models query content as well as its context within a search session. As a result, queries with similar content and context are mapped into vectors close in the embedding space, which allows expansion of a query via simple K-nearest neighbor search in the projected space. The method was trained on more than 12 billion sessions, one of the largest corpuses reported thus far, and evaluated on both public TREC data set and in-house sponsored search data set. The results show the proposed approach significantly outperformed existing state-of-the-art, strongly indicating its benefits and the monetization potential.
Starting Page	383
Ending Page	392
Page Count	10
File Format	PDF
ISBN	9781450336215
DOI	10.1145/2766462.2767709
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-08-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Algorithms Query rewriting Information retrieval
Content Type	Text
Resource Type	Article

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