Report:VantagePoint/Text Mining and Clustering/Clustering Unstructured Data via Keyword Extraction

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System Data
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Major Recent Updates
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Searching
Data Integration
Importing Data
- Supported Data Types
- Supported File Formats
- The Importing Process
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- Filtering or Automated Data Extraction
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- Annotating Data with User Defined Parameters
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Advanced Automated Features
- Assignee Prediction
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Text Mining and Clustering
- Clustering Structured Data
- Clustering Unstructured Data via Keyword Extraction
- Natural Language Processing
- Mapping Document Clusters
- Evolving Clusters through Time
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<< Clustering Structured Data | Natural Language Processing >>

Clustering Unstructured Data via Keyword Extraction

Patent analytics expert Anthony Trippe explains clustering unstructured data via keyword extraction. "Unstructured text is defined as text that has not been indexed or segmented into individual data fields. The only structure contained within the document is the structure that was implied by the author when they put words into sentences, sentences into paragraphs, and so on…As with the clustering of structured data, text concepts instead of codes can then be used to group documents that share a high degree of overlap…Where tools for clustering tagged or structured data start by parsing the fielded data into a database, the systems for clustering unstructured text begin by identifying relevant terms within a document." ^[1]

Clustering of unstructured data via keyword extraction is available using the Extract Nearby Phrase command. See the Natural Language Processing section for more details.

Sources

↑ Trippe, Anthony J. "Patinformatics: Tasks to tools." World Patent Information 25 (2003): 211-221.

[1] Trippe, Anthony J. "Patinformatics: Tasks to tools." World Patent Information 25 (2003): 211-221.

[1]

Report:VantagePoint/Text Mining and Clustering/Clustering Unstructured Data via Keyword Extraction

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Clustering Unstructured Data via Keyword Extraction

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