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Topicalizer API

Note: The Topicalizer API is no longer available.
This profile is retained for historical purposes only.

Topicalizer is a text analysis and topic extraction tool. Based on methods of computational linguistics it provides various analyses for a given URL or plain text. These comprise, amongst others, language recognition, lexical density, keywords, collocations, word and phrase frequencies, readability and a short abstract. Topicalizer can, for instance, be used for automatically tagging a website or blog entry with semantic information or for retrieving summaries for web pages.

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Topicalizer: Highlights

Summary: Document analysis service

Category: Other

Tags: tagging deadpool

Protocols: REST

Data Formats: XML

API home: http://www.topicalizer.com/api/

Topicalizer: Specifications

Functionality

Client Install Required: No

Service Endpoint: http://www.topicalizer.com/api/

Signup and Licensing

Signup Requirements: None

Developer Key Required

Account Required

Commercial Licensing

Provider: topicalizer.com

Non-Commercial Lic.

Data Licensing

Usage Fees

Program Fees

Certification Program

Usage Limits

Terms of Service: General Terms of Service

Security

Authentication Model: None

SSL Support

Read-only Without Login: Yes

Support

Vendor API Kits

Community API Kits

API Blog

Site Blog

API Forum

Developer Support

Console URL

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Mashups, Developers & Source Code

Mashups using Topicalizer[ Add a mashup ]

Developers using Topicalizer[ Add me ]

Source Code for Topicalizer[ Add a source code link ]

There are no source code libraries or how-to links for Topicalizer. If you know one why not add it?

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Comments

December 02, 2006 at 12:29: Comment by: Björn Wilmsmann
The Topicalizer API now sports yet another method named getSemWeb, which build a web of related terms for a given term by making use of the Google API und Wikipedia.

May 04, 2006 at 01:06: Comment by: Björn Wilmsmann
The Topicalizer API now has a another new method called getCoOccurrences, which makes use of large corpora of different text categories in order to guess, which words co-occur most frequently with a given text.