• Publications
  • Influence
Graph-Based Wrong IsA Relation Detection in a Large-Scale Lexical Taxonomy
TLDR
We study the problem of improving the quality for automatically constructed web-scale knowledge bases, in particular, lexical taxonomies of isA relationships. Expand
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Learning Defining Features for Categories
TLDR
We formalize the defining feature learning problem and propose a bootstrapping solution to learn defining features from features of entities belonging to a category. Expand
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Cross-Lingual Type Inference
TLDR
We propose a multi-label hierarchical classification algorithm to type Chinese entities with DBpedia types. Expand
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On the Transitivity of Hypernym-Hyponym Relations in Data-Driven Lexical Taxonomies
TLDR
We introduce a supervised approach to detect whether transitivity holds for any given pair of hypernym-hyponym relationships for data-driven lexical taxonomies. Expand
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Probase+: Inferring Missing Links in Conceptual Taxonomies
TLDR
We use a state-of-the-art data-driven conceptual taxonomy, Probase, to show that missing links in taxonomies are the chief problem that hinders their adoption by many real life applications, for the missing links break the inferencing that the taxonomy claims to support. Expand
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Evidence-based Trustworthiness
TLDR
We develop a general framework for estimating the trustworthiness of information sources in an environment where multiple sources provide claims and supporting evidence, and each claim can potentially be produced by multiple sources. Expand
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Finding Related Tables in Data Lakes for Interactive Data Science
TLDR
We develop search and management solutions for the Jupyter Notebook data science platform, to enable scientists to augment training data, find potential features to extract, clean data, and find joinable or linkable tables. Expand
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Dataset Relationship Management
TLDR
The database community has largely focused on providing improved transaction management and query capabilities over records (and generalizations thereof). Expand
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Entity Suggestion with Conceptual Expanation
Entity Suggestion with Conceptual Explanation (ESC) refers to a type of entity acquisition query in which a user provides a set of example entities as the query and obtains in return not only someExpand
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Juneau: Data Lake Management for Jupyter
TLDR
In collaborative settings such as multi-investigator laboratories, data scientists need improved tools to manage not their data records but rather their data sets and data products, to facilitate both provenance tracking and data reuse within their data lakes and file systems. Expand
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