basketballsunsky.blogg.se - Mac search for a document based on text

#Mac search for a document based on text how to
#Mac search for a document based on text full
#Mac search for a document based on text code

Text patterns (Regular Expressions): Extraction of structured data or data enrichment with text patterns (regular expressions) can extract informations like email-adresses or amounts of money.Annotation & Tagging: Tags from (collaborative) annotations and tagging.They can be managed in plaintext lists, databases, ontologies, thesauri or in the thesaurus user interface for dictionary based or thesaurus based text mining and thesaurus based faceted search Lists of Named Entities: Listed known named entities like organizations, persons, locations or concepts.This structure will be generated and facets/fields are valued with data from the following analysis: With the faceted search you can see an aggregated overview for the different facets like paths, concepts, persons, locations or organzations showing, how many documents matching the named entities. If you do not enter a search query and don't use a filters it shows the words which are contained in the most of all indexed documents. The view Words (option of the tab/button Analyze) shows you the words which are contained in the most documents of the results of your search context (documents matching your search query and filters). If you don't want to analyze all indexed documents, you can search and filter the context you want to mine and analyze. Search and filter the interesting documents It can be used as integrated text mining toolbox for text datamining (TDM) for semi-automated or automated text analysis, document mining, text comparision, text visualization and topic modelling to get useful analysis results even of unknown data sources.

#Mac search for a document based on text full

So you can use the search engine not only for information retrieval by full text search to search and find known issues or to get structured data from unstructured data sources or texts by information extraction. On this base and index you can search, review, filter, analyze and mine content with different text mining, analysis, extraction, data mining and clustering methods. The search engine extracts automatically texts of different file formats and uses grammar rules (stemming) to index and find different word forms. Text data mining (TDM) by text analysis, information extraction, document mining, text comparison, text visualization and topic modelling

#Mac search for a document based on text code

Source code and open source development.

#Mac search for a document based on text how to

How to develop your own data enrichment plugins with python.

Extract data by text patterns (regular expressions).

Web scraper (ETL of structured data from HTML).

Optimizing performance & scaling (parallel processing & server cluster).

Rules for automatic tagging or classification.

Lists, Dictionaries, Vocabularies and Thesauri (Ontologies).

Vocabulary & Thesaurus (dictionary of names or concepts, aliases, synonyms & relations).

Analyze massive leaks for investigative reporting.

Network analysis, connections & relations (graph).

Text analytics: Text Mining and Content Analysis.

Aggregated overview of named entities like persons, organizations, locations or concepts (faceted search).