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  1. Journal of Computer Science and Technology
  2. Journal of Computer Science and Technology : Volume 25
  3. Journal of Computer Science and Technology : Volume 25, Issue 3, May 2010
  4. Context-Sensitive Document Ranking
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Journal of Computer Science and Technology : Volume 32
Journal of Computer Science and Technology : Volume 31
Journal of Computer Science and Technology : Volume 30
Journal of Computer Science and Technology : Volume 29
Journal of Computer Science and Technology : Volume 28
Journal of Computer Science and Technology : Volume 27
Journal of Computer Science and Technology : Volume 26
Journal of Computer Science and Technology : Volume 25
Journal of Computer Science and Technology : Volume 25, Issue 6, November 2010
Journal of Computer Science and Technology : Volume 25, Issue 5, September 2010
Journal of Computer Science and Technology : Volume 25, Issue 4, July 2010
Journal of Computer Science and Technology : Volume 25, Issue 3, May 2010
Preface
Outlier Detection over Sliding Windows for Probabilistic Data Streams
Privacy-Preserving Data Sharing in Cloud Computing
Efficient Location Updates for Continuous Queries over Moving Objects
Towards Progressive and Load Balancing Distributed Computation: A Case Study on Skyline Analysis
Context-Sensitive Document Ranking
The Inverse Classification Problem
Annotation Based Query Answer over Inconsistent Database
HAPS: Supporting Effective and Efficient Full-Text P2P Search with Peer Dynamics
A Solution of Data Inconsistencies in Data Integration — Designed for Pervasive Computing Environment
Flash-Optimized B+-Tree
Efficient Distributed Skyline Queries for Mobile Applications
A Query Interface Matching Approach Based on Extended Evidence Theory for Deep Web
Dynamic Damage Recovery for Web Databases
Harmonic Field Based Volume Model Construction from Triangle Soup
Making Slide Shows with Zoomquilts
Model Transduction for Triangle Meshes
Feature Preserving Mesh Simplification Using Feature Sensitive Metric
Geometry Texture Synthesis Based on Laplacian Texture Image
Geometric Bone Modeling: From Macro to Micro Structures
Nonlocal-Means Image Denoising Technique Using Robust M-Estimator
Multilevel Threshold Based Image Denoising in Curvelet Domain
A New Classifier for Facial Expression Recognition: Fuzzy Buried Markov Model
Journal of Computer Science and Technology : Volume 25, Issue 2, March 2010
Journal of Computer Science and Technology : Volume 25, Issue 1, January 2010
Journal of Computer Science and Technology : Volume 24
Journal of Computer Science and Technology : Volume 23
Journal of Computer Science and Technology : Volume 22
Journal of Computer Science and Technology : Volume 21
Journal of Computer Science and Technology : Volume 20
Journal of Computer Science and Technology : Volume 19
Journal of Computer Science and Technology : Volume 18
Journal of Computer Science and Technology : Volume 17
Journal of Computer Science and Technology : Volume 16
Journal of Computer Science and Technology : Volume 15
Journal of Computer Science and Technology : Volume 14
Journal of Computer Science and Technology : Volume 13
Journal of Computer Science and Technology : Volume 12

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Context-Sensitive Document Ranking

Content Provider SpringerLink
Author Chang, Li Jun Xu Yu, Jeffrey Qin, Lu
Copyright Year 2010
Abstract Ranking is a main research issue in IR-styled keyword search over a set of documents. In this paper, we study a new keyword search problem, called context-sensitive document ranking, which is to rank documents with an additional context that provides additional information about the application domain where the documents are to be searched and ranked. The work is motivated by the fact that additional information associated with the documents can possibly assist users to find more relevant documents when they are unable to find the needed documents from the documents alone. In this paper, a context is a multi-attribute graph, which can represent any information maintained in a relational database, where multi-attribute nodes represent tuples, and edges represent primary key and foreign key references among nodes. The context-sensitive ranking is related to several research issues, how to score documents, how to evaluate the additional information obtained in the context that may contribute to the document ranking, how to rank the documents by combining the scores/costs from the documents and the context. More importantly, the relationships between documents and the information stored in a relational database may be uncertain, because they are from different data sources and the relationships are determined systematically using similarity match which causes uncertainty. In this paper, we concentrate ourselves on these research issues, and provide our solution on how to rank the documents in a context where there exist uncertainty between the documents and the context. We confirm the effectiveness of our approaches by conducting extensive experimental studies using real datasets. We present our findings in this paper.
Starting Page 444
Ending Page 457
Page Count 14
File Format PDF
ISSN 10009000
Journal Journal of Computer Science and Technology
Volume Number 25
Issue Number 3
e-ISSN 18604749
Language English
Publisher Springer US
Publisher Date 2010-05-08
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword document ranking uncertain ranking structure cost similarity Information Systems Applications (incl.Internet) Artificial Intelligence (incl. Robotics) Data Structures, Cryptology and Information Theory Theory of Computation Software Engineering Computer Science
Content Type Text
Resource Type Article
Subject Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture
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