Reincke, 2003 - Google Patents
Profiling and classification of scientific documents with SAS Text MinerReincke, 2003
View PDF- Document ID
- 17812926176005621854
- Author
- Reincke U
- Publication year
- Publication venue
- third &Knowledge Discovery” Workshop
External Links
Snippet
The automatic classification of documents into categories is an increasingly important task. As in life sciences scientific document collections continue to grow at exponential growth rates, the task of retrieving and classifying the appropriate documents by hand can become …
- 241001106462 Ulmus 0 abstract description 4
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/30707—Clustering or classification into predefined classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
- G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30011—Document retrieval systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99933—Query processing, i.e. searching
- Y10S707/99935—Query augmenting and refining, e.g. inexact access
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US7603348B2 (en) | System for classifying a search query | |
Buntine et al. | Applying discrete PCA in data analysis | |
Barbosa et al. | Combining classifiers to identify online databases | |
US6701305B1 (en) | Methods, apparatus and computer program products for information retrieval and document classification utilizing a multidimensional subspace | |
EP1435581B1 (en) | Retrieval of structured documents | |
US7752204B2 (en) | Query-based text summarization | |
US20040010485A1 (en) | Retrieving, detecting and identifying major and outlier clusters in a very large database | |
Chen et al. | Automated feature weighting in naive bayes for high-dimensional data classification | |
Shu et al. | A neural network-based intelligent metasearch engine | |
Cummins | Document score distribution models for query performance inference and prediction | |
Hull | Information retrieval using statistical classification | |
Ding et al. | User modeling for personalized Web search with self‐organizing map | |
US20040186833A1 (en) | Requirements -based knowledge discovery for technology management | |
Phadnis et al. | Framework for document retrieval using latent semantic indexing | |
Nanas et al. | A comparative evaluation of term weighting methods for information filtering | |
Reincke | Profiling and classification of scientific documents with SAS Text Miner | |
McCarey et al. | Recommending library methods: An evaluation of the vector space model (VSM) and latent semantic indexing (LSI) | |
Vadivel et al. | An Effective Document Category Prediction System Using Support Vector Machines, Mann-Whitney Techniques | |
Negm et al. | Investigate the performance of document clustering approach based on association rules mining | |
Trieschnigg et al. | Hierarchical topic detection in large digital news archives | |
Yang et al. | Decomposition of term-document matrix representation for clustering analysis | |
Regulski | Formalization of technological knowledge in the field of metallurgy using document classification tools supported with semantic techniques | |
Cheng et al. | Learning to rank relevant documents for information retrieval in bioengineering text corpora | |
Imran et al. | Selecting Effective Expansion Terms for Better Information Retrieval. | |
Samundeeswari | Comparison of neural networks and support vector machines using PCA and ICA for feature reduction |