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Xiaomin Ning

dblp:94/4678 · DBLP profile ↗
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7ranked-venue papers
2as first author
0since 2021 · last 2009
—ORCID · none

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

Databases, data management, data science and information retrieval · 3 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1

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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › distributed information retrieval
peer-to-peer search
0.112006
Efficient search for peer-to-peer information retrieval using semantic small world · WWW 2006
Distributed systems
peer-to-peer systems
0.112006
Efficient search for peer-to-peer information retrieval using semantic small world · WWW 2006
Distributed systems › peer-to-peer systems › peer-to-peer search
unstructured p2p search
0.112006
Efficient search for peer-to-peer information retrieval using semantic small world · WWW 2006

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

small-world network · 0.1
YearPublicationVenuePosition
2009 Practical and effective IR-style keyword search over semantic web
Xiaomin Ning, Hai Jin 0001, Weijia Jia 0001, Pingpeng Yuan
Inf. Process. Manag.1
2008 A Suggested Framework for Exploring Contextual Information to Evaluate and Recommend Services
Hao Wu 0010, Fei Luo 0002, Xiaomin Ning, Hai Jin 0001
GPC3
2008 RSS: A framework enabling ranked search on the semantic web
Xiaomin Ning, Hai Jin 0001, Hao Wu 0010
Inf. Process. Manag.1
2008 Combining weights with fuzziness for intelligent semantic web search
Hai Jin 0001, Xiaomin Ning, Weijia Jia 0001, Hao Wu 0010, Guilin Lu
Knowl. Based Syst.2
2007 Improving Search in Peer-to-Peer Literature Sharing Systems via Semantic Small World
abstract
Efficient search for unstructured peer-to-peer information retrieval systems is a challenging problem. This paper proposes a semantic overlay based on the small world phenomenon that facilitates efficient search for information retrieval in unstructured P2P systems. In the semantic overlay, each node maintains a number of short-range links which are semantically similar to the node, together with a small collection of long-range links that help increase recall rate of information retrieval as well as reduce network traffic. In this paper we present how to construct and maintain a semantic small world overly, and the search strategy utilizing the above semantic overlay. Experimental results show that our model can improve performance by 150% compared to Gnutella and by up to 50% compared to the Interest-based model, a similar shortcut-based search technique
Hai Jin 0001, Xiaomin Ning
PDP2
2006 Efficient search for peer-to-peer information retrieval using semantic small world
abstract
This paper proposes a semantic overlay based on the small world phenomenon that facilitates efficient search for information retrieval in unstructured P2P systems. In the semantic overlay, each node maintains a number of short-range links which are semantically similar to each other, together with a small collection of long-range links that help increasing recall rate of information retrieval and reduce network traffic as well. Experimental results show that our model can improve performance by 150% compared to Gnutella and by up to 60% compared to the Interest-based model - a similar shortcut-based search technique.
Hai Jin 0001, Xiaomin Ning, Hanhua Chen
WWW2
2006 Facilitating Service Discovery with Semantic Overlay
Hai Jin 0001, Hao Wu 0010, Xiaomin Ning
J. Comput. Sci. Technol.3