
Multidisciplinary Information Retrieval
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions

Content
- Title
- Preface
- Organization
- Table of Contents
- Patent Search
- Learning-Based Pseudo-Relevance Feedback for Patent Retrieval
- Introduction
- Related Work
- Establishing a Baseline
- Estimating the Query Model
- Estimating the Relevance Model
- Finding Effective Feedback Documents
- Experimental Methodology and Results
- Experimental Setup
- Usefulness of Effective Feedback Documents
- Predicting the Effectiveness of a Feedback Document
- Parameter Sensitivity
- Conclusions
- Learning-Based Pseudo-Relevance Feedback for Patent Retrieval
- Introduction
- Related Work
- Structural and Topical Dimensions in Patent Text
- Extraction of Parallel Text
- Experimental Data
- Textual Similarities across IPC Domains
- Cross-Domain Translation
- Compound Splitting on Textual Domains
- Discussion
- References
- Query Enhancement for Patent Prior-Art-Search Based on Keyterm Dependency Relations and Semantic Tags
- Introduction
- Background and Related Work
- Proposed Query Formulation Method
- System Description
- Term Annotation by Semantic Tags
- Term Weighting by Keyterm Dependency Relations (KDR)
- Query Formulation
- Patent Indexing and Retrieval
- Experiments and Results
- Test Collection and Evaluation Measures
- Experimental Results
- Overall Summary
- Conclusion
- References
- Web Search
- Analysis and Detectionof Web Spam by Means of Web Content
- Introduction
- Related Work
- Detection of Spam by Means of Content Analysis
- Detection of Some Kinds of Web Spam
- SAAD Heuristics for Web Spam Detection
- Method for Web Spam Detection
- Experimental Results
- Dataset
- Experimental Setup
- Results in Web Spam Dataset of Webb
- Results in Web Spam Dataset of Yahoo!
- Conclusions
- Future Work
- References
- Discovery of Environmental Nodes in the Web
- Introduction
- Related Work
- Empirical Study of Environmental Websites
- General Framework
- Web Search
- Basic Queries
- Extended Queries
- Site Post Processing
- Classification
- Textual Features Extraction
- Experimental Study
- Web Search Step
- Classification Step
- Final Results
- Conclusions
- References
- Web Searching with Entity Mining at Query Time
- Introduction
- Background and Related Work
- NEM at Query Time
- On Exploiting Linked Open Data
- Experimental Results
- Comparative Evaluation of Entity Ranking Methods by Users
- Contents Mining versus Snippet Mining
- Linked Data-Related Experimental Results
- Concluding Remarks
- References
- Applications
- Patent and Norm Exploration with the m2n Knowledge Discovery Suite
- Challenges in Patent and Norm Retrieval
- m2n Knowledge Discoverer for Norm and Patent Exploration
- Image Analysis
- Accessing Data
- Summary
- References
- Hierarchical Classification of Web Documents by Stratified Discriminant Analysis
- Introduction
- Related Research
- Linear Discriminant Analysis
- Stratified Discriminant Analysis
- Experimental Analysis
- Dataset
- Models
- Performance Measures
- Results
- Conclusions and Future Work
- References
- PatMedia: Augmenting Patent Search with Content-Based Image Retrieval
- Introduction
- PatMedia Search Engine
- Results and Evaluation
- Results and Quantitative Evaluation
- Patent Search Scenarios and Qualitative Evaluation
- Conclusions
- References
- Query Formulation and Analysis
- Generating Variant Keyword Forms for a Morphologically Complex Language Leads to Successful Information Retrieval with Finnish
- Introduction
- Inflected Keyword Generation for Finnish
- Generators
- Evaluation
- Basic Evaluation
- Evaluation with Other Base Form Creation Method
- Generated Runs in the Lemmatized Index
- Searching with Variant Keyword Forms in the Web
- Discussion and Conclusions
- References
- Analyzing Query Logs of USPTO Examiners to Identify Useful Query Terms in Patent Documents for Query Expansion in Patent Searching: A Preliminary Study
- Introduction
- Related Work
- Query Log Analyses
- Experiment Set Up
- General Statistics
- Acquiring Lexical Knowledge from Patent Documents
- Experiment Set Up
- SFT and Lexical Knowledge Detection
- Conclusions and Future Work
- References
- Discovering Relevant Features for Effective Query Formulation
- Introduction
- Related Work
- Query Formulation
- Phrase Extraction
- Basic Definitions
- Frequent Patterns and Closed Patterns
- Closed Sequential Patterns
- The Pattern Deploying Method
- Our Approach
- Pattern Refinement
- Mining Negative Relevance Feedback
- Selecting Negative Documents
- Feature Extraction
- Evaluation and Discussion
- Experimental Dataset
- Data Preprocessing and Measures
- Baseline Models and Settings
- Minimum Support Thresholds
- Comparison to Pattern-Based Methods
- Comparison to Term-Based Methods
- Conclusion
- References
- Author Index
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.