xAIgent.  Content Key Phrase Extraction Made Easy!

Text, Email, HTML ... from any Text of any Subject domain, the xAIgent RESTful API Automatically turns content of any subject matter into lists of Key Phrases along with their relative rankings including highlighted examples of how those key terms have been used specifically within the target document. Available for English, French, German, Japanese, Korean and Spanish - xAIgent is ready to turn your content into gold.

Ideal for - web text extraction, search optimization (SEO), intelligent text mining, refined search, advanced terror detection, knowledge management (KM), information retrieval (IR), semantic web development, indexing, categorization, cataloguing, inference engines, document management, portal services, speed reading, trend analysis, automatic document tagging, weblog tagging and more...

What is a Key Phrase

For example,  Authors are often requested to provide a list of key words for their articles. We call these key phrases, rather than key words, because they are often phrases of two or more words, rather than single words. A key phrase list is defined as a short list of phrases (typically five to fifteen phrases) that capture the main topics discussed in a given document. Automatic key phrase extraction is defined as the automatic selection of important, topical phrases from within the body of a document. Automatic key phrase extraction is a special case of the more general task of automatic key phrase generation, in which the generated phrases do not necessarily appear in the body of the given document.

Examples of where Key Phrases are used

'The Power Behind DOC TAGS'

Curate Metadata

Many researchers believe that metadata is essential to address the problems of document management. Metadata is meta-information about a document or set of documents. There are several standards for document metadata, including the Dublin Core Metadata Element Set (championed by the US Online Computer Library Center), the MARC (Machine-Readable Cataloging) format (maintained by the US Library of Congress), the GILS (Government Information Locator Service) standard (from the US Office of Social and Economic Data Analysis), and the CSDGM (Content Standards for Digital Geospatial Metadata) standard (from the US Federal Geographic Data Committee). All of these standards include a field for key phrases (although they have different names for this field).

Content and Document Management Systems

Content and Documents being added to a management system must be identified by the subject matter (key phrases) for accurate retrieval. Unless you're the author of that content / document how do you know what the content speaks to? Integrating xAIgent into a Content / Document Management System provides accurate, contextual and objective subject matter key terms which are invaluable for Cataloging, Indexing and for Retrieving the stored information accurately.

Many business rules direct that authors include Document Tags / Summary terms, which are used when adding the content into the system. What happens when the author has not provided the key terms? Or, what if the document was authored prior to the established business rules being in place?  The same holds true in context of the Semantic Web and adhering to those structures and publishing guidelines.  xAIgent becomes a critical tool in the publishing and retrieval of contextually accurate information.

Creating Document Highlights

When we skim a document, we scan for key phrases, to quickly determine the topic of the document. Highlighting is the practice of emphasizing key phrases and key passages (e.g., sentences or paragraphs) by underlining the key text, using a special font, or marking the key text with a special colour. The purpose of highlighting is to facilitate skimming. Automatic key phrase extraction can be used for highlighting and also to enable text-to-speech software to provide audio skimming capability.

Create Indexes

An alphabetical list of key phrases, taken from a collection of documents or from parts of a single long document (chapters in a book), are used for creating indexes.

Interactive Query Refinement

Using a search engine is often an iterative process. The user enters a query, examines the resulting hit list, and modifies the query, then tries again. Most search engines do not have any special features that support the iterative aspect of searching. One approach to interactive query refinement is to take the user's query, fetch the first round of documents, extract key phrases from them, and then display the first round of documents to the user, along with suggested refinements to the first query, based on combinations of the first query with the extracted key phrases.

Research Optimization

Relevant information is critical for the success of any business and providing relevant information in the right context is what gives an organization an ultimate competitive advantage. Rather than working through traditional, time consuming, iterative research processes - engage the Text Mining power of xAIgent to empower information workers with relevant and meaningful results, quickly and accurately.

Feature Highlights:

• Automatically Create Contextually Accurate Tags for a Document

• Automatically Create Contextually Accurate Tags Document Folder

• Automatically Add Document Meta Data Tags

• Subject Domain Agnostic - additional training NOT required

• Automatic Processing - supervision is NOT required

• Document Tags are presented by Weighted Importance

• Process Reporting ...

• Tags Generated

• Documents Processed

• Document Location

• Examine Comparative Document Tags

• Find Documents with 'These' Tags

• Multi Language Support ...

• English

• French

• German

• Japanese

• Korean

• Spanish

• Contextual Key Terms Automatically Extracted for Each Document