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Chapter and Conference Paper
Aggregate Reverse Rank Queries
Recently, reverse rank queries have attracted significant research interest. They have real-life applicability, such as in marketing analysis and product placement. Reverse k-ranks queries return users (prefer...
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Chapter and Conference Paper
Efficient Processing of Aggregate Reverse Rank Queries
Given two data sets of user preferences and product attributes in addition to a set of query products, the aggregate reverse rank (ARR) query returns top-k users who regard the given query products as the high...
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Chapter
Bound-and-Filter Framework for Aggregate Reverse Rank Queries
Finding top-rank products based on a given user’s preference is a user-view rank model that helps users to find their desired products. Recently, another query processing problem named reverse rank query has a...
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Chapter and Conference Paper
NGNC: A Flexible and Efficient Framework for Error-Tolerant Query Autocompletion
Query autocompletion (QAC) is an important feature that automatically completes a query and saves users’ keystrokes. It has been widely adopted in Web search engines, desktop search, input method editors, etc....
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Chapter and Conference Paper
Quality Control for Hierarchical Classification with Incomplete Annotations
Hierarchical classification requires annotations with hierarchical class structures. Although crowdsourcing services are inexpensive ways to collect annotations for hierarchical classification, the results are...
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Chapter and Conference Paper
Entity Matching with String Transformation and Similarity-Based Features
Entity matching is an important task in common data cleaning and data integration problems of determining two records that refer to the same real-world entity. Many research use string similarity as features t...
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Chapter and Conference Paper
CAGAIN: Column Attention Generative Adversarial Imputation Networks
Imputation for missing values is a key operation in building data analysis models. In this paper, we target numerical and categorical values in tabular data. While previous studies have demonstrated the effect...
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Chapter and Conference Paper
QA-Matcher: Unsupervised Entity Matching Using a Question Answering Model
Entity matching (EM) is a fundamental task in data integration, which involves identifying records that refer to the same real-world entity. Unsupervised EM is often preferred in real-world applications, as la...
