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Zengping Tian

dblp:41/187 · DBLP profile ↗
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10ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 6Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
3 papers
Information retrieval · 67% Data integration and cleaning · 26% Database system architecture and tuning · 8%
Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › query processing
web query processing		 0.122000
Toward Learning Based Web Query Processing · VLDB 2000
Fact: A Learning Based Web Query Processing System · SIGMOD Conference 2000
Data integration and cleaning › schema mapping
XML-to-relational mapping		 0.012001
VXMLR: A Visual XML-Relational Database System · VLDB 2001
Natural language and speech › Information extraction and text analysis
web information extraction		 0.012000
Fact: A Learning Based Web Query Processing System · SIGMOD Conference 2000
Information retrieval
web search		 0.012000
Fact: A Learning Based Web Query Processing System · SIGMOD Conference 2000

Methods — techniques the papers use, named apart from their topics

learning from user browsing · 0.1keyword query processing · 0.1machine learning · 0.0
YearPublicationVenuePosition
2001 VXMLR: A Visual XML-Relational Database System
Aoying Zhou, Hongjun Lu, Shihui Zheng, Wenyun Ji, Zengping Tian
 VLDB7
2001 Attribute Value Extraction and Standardization in Data Integration
Hongjun Lu, Zengping Tian
 WAIM2
2000 Fact: A Learning Based Web Query Processing System
abstract
FACT (Fast and ACcuraTe) is a query processing system aimed at providing users with facilities so that they can get the query results from the Web in a database-like fashion. The system takes user queries in the form of keywords (free text) and returns segments of Web pages that contain the required information. It works as follows. The input from a user is passed to a general- purpose search engine to obtain a set of URLs of Web pages that may contain the required information. The system later locates the query results from the Web pages reachable from these URLs. Since queries expressed in keywords may be not able to express query requirements precisely or may not guarantee the discovery of required information inherently, the user is asked to first browse a few pages, during which the system learns from her/him about the exact query requirements and heuristics of finding the required information through a series of hyperlinks. The system will process the rest URLs and present the results in the form of segments of Web pages to the user.
Songting Chen, Yanlei Diao, Hongjun Lu, Zengping Tian
 SIGMOD Conference4
2000 Toward Learning Based Web Query Processing
Yanlei Diao, Hongjun Lu, Songting Chen, Zengping Tian
 VLDB4
2000 Incremental Mining of the Schema of Semistructured Data
Aoying Zhou, Shuigeng Zhou, Weining Qian, Zengping Tian
 J. Comput. Sci. Technol.5
2000 Generalized Multidimensional Association Rules
Aoying Zhou, Shuigeng Zhou, Zengping Tian
 J. Comput. Sci. Technol.4
1999 Incremental Mining of Schema for Semistructured Data
Aoying Zhou, Shuigeng Zhou, Zengping Tian
 PAKDD4
1999 An Improved Definition of Multidimensional Inter-transaction Association Rule
Aoying Zhou, Shuigeng Zhou, Zengping Tian
 PAKDD4
1997 On the expressive power of F-logic language
Zengping Tian, Yunyao Qu, Baile Shi
 J. Comput. Sci. Technol.1
1996 Design and implementation of a concurrency control mechanism in an object-oriented database system
Yunyao Qu, Zengping Tian, Baile Shi
 J. Comput. Sci. Technol.2