Welcome to the Fourth ACM International Conference on Web Search and Data Mining (WSDM 2011) held on February 9-12, 2011, in Hong Kong. As the premier ACM conference in the field, WSDM 2011 offers a highly competitive forum for reporting the latest developments in websearch, social search and data mining. We are pleased to present the proceedings of the conference as its published record.
Although it is only in its fourth year, WSDM has already witnessed significant growth. We received a record 372 submissions, representing a 22% increase compared to WSDM 2010. 19 Senior PC members and 134 PC members conducted reviews to the submissions. The conference accepted 83 papers (22.3% acceptance rate). Among these, 32 papers were selected for oral and poster presentations and 51 papers were selected for poster only presentations. The authors of submitted papers were from 35 countries and regions, authors of accepted papers are from 13 countries and regions. The quality of accepted papers is very high, making WSDM a first tier conference in computer science.
Cited By
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khaledian N and Mardukhi F (2021). CFMT: a collaborative filtering approach based on the nonnegative matrix factorization technique and trust relationships, Journal of Ambient Intelligence and Humanized Computing, 10.1007/s12652-021-03368-6, 13:5, (2667-2683), Online publication date: 1-May-2022.
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Kaligotla C, Yücesan E and Chick S (2020). Diffusion of competing rumours on social media, Journal of Simulation, 10.1080/17477778.2020.1785345, 16:3, (230-250), Online publication date: 4-May-2022.
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Silva C, Galster M and Gilson F (2021). Topic modeling in software engineering research, Empirical Software Engineering, 10.1007/s10664-021-10026-0, 26:6, Online publication date: 1-Nov-2021.
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Yu H and Schroeder S (2017). Distribution and Popularity Patterns of Chinese Music on YouTube: A Case Study of Local Music’s Representation on a Global Internet Platform, Journal of New Music Research, 10.1080/09298215.2017.1369129, 47:1, (68-77), Online publication date: 1-Jan-2018.
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Uitermark J (2016). Complex contention: analyzing power dynamics within Anonymous, Social Movement Studies, 10.1080/14742837.2016.1184136, 16:4, (403-417), Online publication date: 4-Jul-2017.
- Preface Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Introduction Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Background Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Data Understanding Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- MeTA : A Unified Toolkit for Text Data Management and Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Overview of Text Data Access Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Retrieval Models Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Feedback Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Search Engine Implementation Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Search Engine Evaluation Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Web Search Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Recommender Systems Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Overview of Text Data Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Word Association Mining Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Clustering Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Categorization Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Text Summarization Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Topic Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Opinion Mining and Sentiment Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Joint Analysis of Text and Structured Data Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Toward A Unified System for Text Management and Analysis Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- Appendixes Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
- References Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
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Feng Y, Li H and Chen Z Improving Recommendation Accuracy and Diversity via Multiple Social Factors and Social Circles, International Journal of Web Services Research, 10.4018/IJWSR.2014100103, 11:4, (32-46)
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Chen W, Lakshmanan L and Castillo C (2013). Information and Influence Propagation in Social Networks, Synthesis Lectures on Data Management, 10.2200/S00527ED1V01Y201308DTM037, 5:4, (1-177), Online publication date: 27-Oct-2013.
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Al-Rawi A (2017). Viral News on Social Media, Digital Journalism, 10.1080/21670811.2017.1387062, (1-17)
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Han J, Lee S and Cha M (2023). The secret to successful evocative messages: Anger takes the lead in information sharing over anxiety, Communication Monographs, 10.1080/03637751.2023.2236183, (1-21)