Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Jianhan Zhu"'
Autor:
Jianhan Zhu1 j.zhu@open.ac.uk, Gonçalves, Alexandre L.2, Uren, Victoria S.1, Motta, Enrico1, Pacheco, Roberto2, Eisenstadt, Marc1, Dawei Song1
Publikováno v:
Web Intelligence & Agent Systems. Dec2007, Vol. 5 Issue 4, p405-417. 13p. 2 Black and White Photographs, 1 Diagram, 3 Charts.
Publikováno v:
World Patent Information. 33:248-256
There is little need to emphasize the importance of chemoinformatics and chemical information retrieval. However, what seems to require a lot more effort in convincing members of the community is the need for standardized evaluation procedures and me
Publikováno v:
ACM SIGIR Forum. 43:63-70
Over the past decades, significant progress has been made in Information Retrieval (IR), ranging from efficiency and scalability to theoretical modeling and evaluation. However, many grand challenges remain. Recently, more and more attention has been
Publikováno v:
ACM Transactions on Internet Technology. 4:185-208
User traversals on hyperlinks between Web pages can reveal semantic relationships between these pages. We use user traversals on hyperlinks as weights to measure semantic relationships between Web pages. On the basis of these weights, we propose a no
Publikováno v:
Current Challenges in Patent Information Retrieval ISBN: 9783642192302
Current Challenges in Patent Information Retrieval
Current Challenges in Patent Information Retrieval
It has been noted before in this book that patent retrieval is different from, and more complicated than “standard” information retrieval. Evaluation of patent retrieval engines has also been shown to require specific attention. In this chapter,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::711b8dd87b0d0681f1d2d00467976aad
https://doi.org/10.1007/978-3-642-19231-9_5
https://doi.org/10.1007/978-3-642-19231-9_5
Autor:
Jun Wang, Jianhan Zhu
Publikováno v:
SIGIR
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages: the relevance prediction stage and ranking decision stage. During retr
We argue that expert finding is sensitive to multiple document features in an organizational intranet. These document features include multiple levels of associations between experts and a query topic from sentence, paragraph, up to document levels,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fb114cd3caf2311676a401f2a9c06a2
http://oro.open.ac.uk/22129/1/zhu-etal-2009-kais.pdf
http://oro.open.ac.uk/22129/1/zhu-etal-2009-kais.pdf
Autor:
Jianhan Zhu
Publikováno v:
2009 1st IEEE Symposium on Web Society.
Named entities are the basic components for semantic web ontologies and social association networks. How to recognize named entities on a Web scale is challenging due to named entity disambiguation, learning and acquisition of vocabularies and patter
Autor:
Jianhan Zhu, Jun Wang
Publikováno v:
SIGIR
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are dependent between each other. Inspired by the Modern Portfolio Theory, an ec
Publikováno v:
SIGIR
The need for evaluating large amounts of topics (queries) makes IR evaluation an uneasy task. In this paper, we study a topic selection problem for IR evaluation. The selection criterion is based on the overall difficulty of the chosen set, as well a