WSDM '14- Proceedings of the 7th ACM international conference on Web search and data mining

Full Citation in the ACM Digital Library

SESSION: Keynote address

Data that matter: opportunities in crisis informatics research

SESSION: Web search

Improving the efficiency of multi-site web search engines

A self-adapting latency/power tradeoff model for replicated search engines

Heterogeneous graph-based intent learning with queries, web pages and Wikipedia concepts

Exploiting user disagreement for web search evaluation: an experimental approach

Improving search relevance for short queries in community question answering

Struggling or exploring?: disambiguating long search sessions

Democracy is good for ranking: towards multi-view rank learning and adaptation in web search

SESSION: Web Search and advertising

Relative confidence sampling for efficient on-line ranker evaluation

Adapting deep RankNet for personalized search

Search engine click spam detection based on bipartite graph propagation

Sampling dilemma: towards effective data sampling for click prediction in sponsored search

Exploiting contextual factors for click modeling in sponsored search

Predicting response in mobile advertising with hierarchical importance-aware factorization machine

Partner tiering in display advertising

SESSION: Advertising

Estimating ad group performance in sponsored search

Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising

An efficient framework for online advertising effectiveness measurement and comparison

LASER: a scalable response prediction platform for online advertising

SESSION: Log analysis

Discovering common motifs in cursor movement data for improving web search

Modeling dwell time to predict click-level satisfaction

User modeling in search logs via a nonparametric bayesian approach

The last click: why users give up information network navigation

Lessons from the journey: a query log analysis of within-session learning

Scalable K-Means by ranked retrieval

SESSION: Recommender systems

Taxonomy discovery for personalized recommendation

Who likes it more?: mining worth-recommending items from long tails by modeling relative preference

On building entity recommender systems using user click log and freebase knowledge

SESSION: Recommender systems and networks

Improving pairwise learning for item recommendation from implicit feedback

Personalized entity recommendation: a heterogeneous information network approach

Social collaborative retrieval

Transferring heterogeneous links across location-based social networks

Customized tour recommendations in urban areas

SESSION: Networks: communities and labeling

Detecting cohesive and 2-mode communities indirected and undirected networks

FENNEL: streaming graph partitioning for massive scale graphs

A few good predictions: selective node labeling in a social network

Active learning for networked data based on non-progressive diffusion model

Learning latent representations of nodes for classifying in heterogeneous social networks

SESSION: Networks: centrality and influence

Prediction in a microblog hybrid network using bonacich potential

Learning social network embeddings for predicting information diffusion

Modeling opinion dynamics in social networks

Fast approximation of betweenness centrality through sampling

Effective co-betweenness centrality computation

SESSION: Natural language processing; topic models

Chinese-English mixed text normalization

Sentiment analysis on evolving social streams: how self-report imbalances can help

Entity linking at the tail: sparse signals, unknown entities, and phrase models

Latent dirichlet allocation based diversified retrieval for e-commerce search

Supervised N-gram topic model

Going beyond Corr-LDA for detecting specific comments on news & blogs

Nonparametric bayesian upstream supervised multi-modal topic models

SESSION: Topic models; linked data

Spatial compactness meets topical consistency: jointly modeling links and content for community detection

Scalable topic-specific influence analysis on microblogs

WebChild: harvesting and organizing commonsense knowledge from the web

Using linked data to mine RDF from wikipedia's tables

Knowledge-based graph document modeling

Trust, but verify: predicting contribution quality for knowledge base construction and curation

Modelling growth of urban crowd-sourced information

SESSION: Peer production: data analysis

Inferring the impacts of social media on crowdfunding

Understanding and promoting micro-finance activities in

Who watches (and shares) what on youtube? and when?: using twitter to understand youtube viewership

Detecting non-gaussian geographical topics in tagged photo collections

Ranking in heterogeneous social media

Visualizing brand associations from web community photos

Is a picture really worth a thousand words?: - on the role of images in e-commerce

SESSION: Doctoral consortium

Integration of large scale knowledge bases using probabilistic graphical models

Strategy in action: analyzing online search behavior bymining search strategies

On discovering non-obvious recommendations: using unexpectedness and neighborhood selection methods in collaborative filtering systems

Exploratory search with semantic transformations using collaborative knowledge bases

Search by multiple examples


Behavioral data mining and network analysis in massive online games

Exploration and mining of web repositories

Big graph mining for the web and social media: algorithms, anomaly detection, and applications

Diversity and novelty in web search, recommender systems and data streams

Multilingual probabilistic topic modeling and its applications in web mining and search

Entity linking and retrieval for semantic search

WORKSHOP SESSION: Workshop summaries

Log-based personalization: the 4th web search click data (WSCD) workshop

Web-scale classification: web classification in the big data era

1st workshop on diffusion networks and cascade analytics

Workshop on large-scale and distributed systems for information retrieval (LSDS-IR 2014)

Data design for personalization: current challenges and emerging opportunities