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Im Werk suchen
On information need and categorizing search / Sven Meyer zu Eißen. 2007
Inhalt
Notation
Introduction
Thesis Contributions
Thesis Overview
Document Representation and Retrieval
The Information Retrieval Process
Document Representation
Term Vector Models
Document Similarity
Index Term Set Construction Methods
Techniques for Information Need Satisfaction
Information Need and Categorizing Search
Supervised vs. Unsupervised Categorization
The Cluster Hypothesis
Clustering Documents
Challenges
Clustering Algorithms
On the Validity of Document Clusterings
External Cluster Validity Measures
Internal Cluster Validity Measures
Statistical Hypothesis Testing
Experimental Evaluation
Concluding Remarks
The Suffix Tree Document Representation
Suffix Trees
A Closer Look to the Suffix Tree Document Model
Experimental Evaluation
Concluding Remarks
Topic Identification
Formal Framework
Related Work
The WCC Algorithm for Topic Identification
Experimental Evaluation
Concluding Remarks
Genre Classification
What Does Genre Mean?
What Does Genre Mean in the WWW?
Existing Work
User Study and Genre Selection
Features for Genre Classification
Experimental Evaluation
Concluding Remarks
Tira: A Software Architecture for Personal IR
From IR Theory to IR Software
Specification of IR Processes
Petri Nets
Data Flow Graphs and Control/Data Flow Graphs
UML Activity Diagrams
Operationalizing IR Processes with Tira
From PIM to PSM
The Tira Middleware Platform
Tira at Work
Concluding Remarks
Conclusion and Outlook
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