Product information search has become one of the most important application areas of the Web. Especially considering pricey technical products, consumers tend to carry out intensive research activities previous to the actual acquisition for creating an all-embracing view on the product of interest. Federated search backed by ontology-based product information representation shows great promise for easing this research process.
The topic of this thesis is to develop a comprehensive technique for locating, extracting, and integrating information of arbitrary technical products in a widely unsupervised manner. The resulting homogeneous information sets allow a potential consumer to effectively compare technical products based on an appropriate federated product information system.:1. Introduction
1.1. Online Product Information Research
1.1.1. Current Online Product Information Research
1.1.2. Aspired Online Product Information Research
1.2. Federated Shopping Portals
1.3. Research Questions
1.4. Approach and Theses
1.4.1. Approach
1.4.2. Theses
1.4.3. Requirements
1.5. Goals and Non-Goals
1.5.1. Goals
1.5.2. Non-Goals
1.6. Contributions
1.7. Structure
2. Federated Information Systems
2.1. Information Access
2.1.1. Document Retrieval
2.1.2. Federated Search
2.1.3. Federated Ranking
2.2. Information Extraction
2.2.1. Information Extraction from Structured Sources
2.2.2. Information Extraction from Unstructured Sources
2.2.3. Information Extraction from Semi-structured Sources
2.3. Information Integration
2.3.1. Ontologies
2.3.2. Ontology Matching
2.4. Information Presentation
2.5. Product Information
2.5.1. Product Information Source Characteristics
2.5.2. Product Information Source Types
2.5.3. Product Information Integration Types
2.5.4. Product Information Types
2.6. Conclusions
3. A Federated Product Information System
3.1. Finding Basic Product Information
3.2. Enriching Product Information
3.3. Administrating Product Information
3.4. Displaying Product Information
3.5. Conclusions
4. Product Information Extraction from the Web
4.1. Vendor Product Information Search
4.1.1. Vendor Product Information Ranking
4.1.2. Vendor Product Information Extraction
4.2. Producer Product Information Search
4.2.1. Producer Product Document Retrieval
4.2.2. Producer Product Information Extraction
4.3. Third-Party Product Information Search
4.4. Conclusions
5. Product Information Integration for the Web
5.1. Product Representation
5.1.1. Domain Product Ontology
5.1.2. Application Product Ontology
5.1.3. Product Ontology Management
5.2. Product Categorization
5.3. Product Specifications Matching
5.3.1. General Procedure
5.3.2. Elementary Matchers
5.3.3. Evolutionary Matcher
5.3.4. Naïve Bayes Matcher
5.3.5. Result Selection
5.4. Product Specifications Normalization
5.4.1. Product Specifications Atomization
5.4.2. Product Specifications Value Normalization
5.5. Product Comparison
5.6. Conclusions
6. Evaluation
6.1. Implementation
6.1.1. Offers Service
6.1.2. Products Service
6.1.3. Snippets Service
6.1.4. Fedseeko
6.1.5. Fedseeko Browser Plugin
6.1.6. Fedseeko Mobile
6.1.7. Lessons Learned
6.2. Evaluation
6.2.1. Evaluation Measures
6.2.2. Gold Standard
6.2.3. Product Document Retrieval
6.2.4. Product Specifications Extraction
6.2.5. Product Specifications Matching
6.2.6. Comparison with Competitors
6.3. Conclusions
7. Conclusions and Future Work
7.1. Summary
7.2. Conclusions
7.3. Future Work
A. Pseudo Code and Extraction Properties
A.1. Pseudo Code
A.2. Extraction Algorithm Properties
A.2.1. Clustering Properties
A.2.2. Purging Properties
A.2.3. Dropping Properties
B. Fedseeko Screenshots
B.1. Offer Search
B.2. Product Comparison / Die Produktinformationssuche hat sich zu einem der bedeutendsten Themen im Web entwickelt. Speziell im Bereich kostenintensiver technischer Produkte führen potenzielle Konsumenten vor dem eigentlichen Kauf des Produkts langwierige Recherchen durch um einen umfassenden Überblick für das Produkt von Interesse zu erlangen. Die föderierte Suche in Kombination mit ontologiebasierter Produktinformationsrepräsentation stellt eine mögliche Lösung dieser Problemstellung dar.
Diese Dissertation stellt Techniken vor, die das automatische Lokalisieren, Extrahieren und Integrieren von Informationen für beliebige technische Produkte ermöglichen. Die resultierenden homogenen Produktinformationen erlauben einem potenziellen Konsumenten, zugehörige Produkte effektiv über ein föderiertes Produktinformationssystem zu vergleichen.:1. Introduction
1.1. Online Product Information Research
1.1.1. Current Online Product Information Research
1.1.2. Aspired Online Product Information Research
1.2. Federated Shopping Portals
1.3. Research Questions
1.4. Approach and Theses
1.4.1. Approach
1.4.2. Theses
1.4.3. Requirements
1.5. Goals and Non-Goals
1.5.1. Goals
1.5.2. Non-Goals
1.6. Contributions
1.7. Structure
2. Federated Information Systems
2.1. Information Access
2.1.1. Document Retrieval
2.1.2. Federated Search
2.1.3. Federated Ranking
2.2. Information Extraction
2.2.1. Information Extraction from Structured Sources
2.2.2. Information Extraction from Unstructured Sources
2.2.3. Information Extraction from Semi-structured Sources
2.3. Information Integration
2.3.1. Ontologies
2.3.2. Ontology Matching
2.4. Information Presentation
2.5. Product Information
2.5.1. Product Information Source Characteristics
2.5.2. Product Information Source Types
2.5.3. Product Information Integration Types
2.5.4. Product Information Types
2.6. Conclusions
3. A Federated Product Information System
3.1. Finding Basic Product Information
3.2. Enriching Product Information
3.3. Administrating Product Information
3.4. Displaying Product Information
3.5. Conclusions
4. Product Information Extraction from the Web
4.1. Vendor Product Information Search
4.1.1. Vendor Product Information Ranking
4.1.2. Vendor Product Information Extraction
4.2. Producer Product Information Search
4.2.1. Producer Product Document Retrieval
4.2.2. Producer Product Information Extraction
4.3. Third-Party Product Information Search
4.4. Conclusions
5. Product Information Integration for the Web
5.1. Product Representation
5.1.1. Domain Product Ontology
5.1.2. Application Product Ontology
5.1.3. Product Ontology Management
5.2. Product Categorization
5.3. Product Specifications Matching
5.3.1. General Procedure
5.3.2. Elementary Matchers
5.3.3. Evolutionary Matcher
5.3.4. Naïve Bayes Matcher
5.3.5. Result Selection
5.4. Product Specifications Normalization
5.4.1. Product Specifications Atomization
5.4.2. Product Specifications Value Normalization
5.5. Product Comparison
5.6. Conclusions
6. Evaluation
6.1. Implementation
6.1.1. Offers Service
6.1.2. Products Service
6.1.3. Snippets Service
6.1.4. Fedseeko
6.1.5. Fedseeko Browser Plugin
6.1.6. Fedseeko Mobile
6.1.7. Lessons Learned
6.2. Evaluation
6.2.1. Evaluation Measures
6.2.2. Gold Standard
6.2.3. Product Document Retrieval
6.2.4. Product Specifications Extraction
6.2.5. Product Specifications Matching
6.2.6. Comparison with Competitors
6.3. Conclusions
7. Conclusions and Future Work
7.1. Summary
7.2. Conclusions
7.3. Future Work
A. Pseudo Code and Extraction Properties
A.1. Pseudo Code
A.2. Extraction Algorithm Properties
A.2.1. Clustering Properties
A.2.2. Purging Properties
A.2.3. Dropping Properties
B. Fedseeko Screenshots
B.1. Offer Search
B.2. Product Comparison
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:25690 |
| Date | 09 September 2011 |
| Creators | Walther, Maximilian Thilo |
| Contributors | Schill, Alexander, Linnhoff-Popien, Claudia, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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