Context-aware Semantics-based Information Retrieval
By Carsten Keßler

"Context-aware Semantics-based Information Retrieval" was published by IOS Press in 2010 - Amsterdam : Heidelberg, Germany and it has 150 pages.
“Context-aware Semantics-based Information Retrieval” Metadata:
- Title: ➤ Context-aware Semantics-based Information Retrieval
- Author: Carsten Keßler
- Number of Pages: 150
- Publisher: IOS Press
- Publish Date: 2010
- Publish Location: ➤ Amsterdam : Heidelberg, Germany
“Context-aware Semantics-based Information Retrieval” Subjects and Themes:
- Subjects: ➤ geoinformatics - thesis - PhD - Semantic Web - context - Semantic computing - Querying (Computer science) - Database searching
Edition Specifications:
- Format: Paperback
- Weight: 8 ounces
- Dimensions: 9.4 x 6.3 x 0.4 inches
Edition Identifiers:
- The Open Library ID: OL24623248M - OL15698691W
- Library of Congress Control Number (LCCN): 2010485559
- ISBN-13: 9781607506355 - 9783898386425
- ISBN-10: 1607506351
- All ISBNs: 1607506351 - 9781607506355 - 9783898386425
AI-generated Review of “Context-aware Semantics-based Information Retrieval”:
"Context-aware Semantics-based Information Retrieval" Table Of Contents:
- 1- Introduction and Motivation
- 2- Information retrieval as a cornerstone of the information society
- 3- The inherent context-dependence of information retrieval
- 4- Hypothesis and research questions
- 5- Expected results and contribution
- 6- Application scenario
- 7- Methodology and outline
- 8- Related Work and Methodic Background
- 9- Semantics and ontology
- 10- Information retrieval
- 11- Semantic Web
- 12- Context
- 13- Cognitive engineering
- 14- Statistical correlation measures
- 15- Identification of Relevant Context Information
- 16- Motivation
- 17- DIR approach
- 18- Formalization
- 19- Human Participants Test
- 20- Test one: Judgment by order
- 21- Test two: Judgment by numbers
- 22- Results & discussion
- 23- A Context Model for Semantics-based Information Retrieval
- 24- Requirements analysis: Characteristics of a context model
- 25- User model
- 26- Linking to real-world sensors
- 27- Discussion
- 28- 79
- 29- Identification of relevant context information
- 30- User interface
- 31- Server-side implementation
- 32- Conclusions and Future Work
- 33- Summary and discussion
- 34- Application areas
- 35- Future work
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