Crowdsourcing has been established as an essential means to scale human computation in diverse Web applications, reaching from data integration to information retrieval. Yet, crowd workers have wide-ranging levels of expertise. Large worker populations are heterogeneous and comprise a significant amount of faulty workers. As a consequence, quality ...
Published in The VLDB Journal
Set similarity join, which finds all the similar set pairs from two collections of sets, is a fundamental problem with a wide range of applications. Existing works study both exact set similarity join and approximate similarity join problems. In this paper, we focus on the exact set similarity join problem. The existing solutions for exact set simi...
Published in The VLDB Journal
The Resource Description Framework (RDF) is a W3C standard for representing graph-structured data, and SPARQL is the standard query language for RDF. Recent advances in information extraction, linked data management and the Semantic Web have led to a rapid increase in both the volume and the variety of RDF data that are publicly available. As busin...
Published in The VLDB Journal
Relational learning algorithms learn the definition of a new relation in terms of existing relations in the database. The same database may be represented under different schemas for various reasons, such as efficiency, data quality, and usability. Unfortunately, the output of current relational learning algorithms tends to vary quite substantially...
Published in The VLDB Journal
Social networks offer various services such as recommendations of social events, or delivery of targeted advertising material to certain users. In this work, we focus on a specific type of services modeled as constrained graph partitioning (CGP). CGP assigns users of a social network to a set of classes with bounded capacities so that the similarit...
Published in The VLDB Journal
Social media recommendation has attracted great attention due to its wide applications in online advertisement and entertainment, etc. Since contexts highly affect social user preferences, great effort has been put into context-aware recommendation in recent years. However, existing techniques cannot capture the optimal context information that is ...
Published in The VLDB Journal
User data is becoming increasingly available in multiple domains ranging from the social Web to retail store receipts. User data is described by user demographics (e.g., age, gender, occupation) and user actions (e.g., rating a movie, publishing a paper, following a medical treatment). The analysis of user data is appealing to scientists who work o...
Published in The VLDB Journal
With the prominence of location-based services and social networks in recent years, huge amounts of spatio-temporal document collections (e.g., geo-tagged tweets) have been generated. These data collections often imply user’s ideas on different products and thus are helpful for business owners to explore hot topics of their brands and the competiti...
Published in The VLDB Journal
