Latent Semantic Indexing

Latent Semantic Indexing, or LSI, is an application used by search engines that analyzes information not only using keywords, but also conceptually. It provides a human-like approach to the search retrieving documents that also contain synonyms and common themes.

Agilex has formed a partnership with Content Analyst Company that has combined the latent semantic indexing (LSI) technology with the application of sophisticated business processes. The result offers you the capability to search the way most people think.

Formerly only available to elite government offices and the Intelligence community, the power of Content Analyst - CAT - is a technology that is now available to you.

• Reduce document search times by over 65%
• Reduce document search times by over 65%
• Sort and categorize your documents in 70% less time
• Save on translation costs by translating only the relevant documents
• Quickly summarize, sort, and search your customer data

CORE FEATURES OF CONTENT ANALYST

Conceptual Search

Virtually "read" every document it indexes and identifies all the concepts instead of tags and keywords.

Why this is better: It's faster than other techniques, it finds information that those techniques can't, and can even use a long document as the "search string".

Who would use this: Any Analyst who is trying to find critical information from documents like emails, Word docs, or Web content.

Automatic Categorization

Uses small sets of examples – 20 or so per category – to find all related or similar documents in large collections.

Why this is better: It’s extremely fast, it can categorize millions of documents per server per day, and it identifies only the documents that are extremely relevant to your examples.

Who would use this: Any Analyst who is trying to sort through large and changeable collections of information on a “real-time” basis.

Automatic Clustering

“Reads” a previously unclassified collection of documents and automatically sorts them into logical groups or clusters.

Why this is better: It doesn't require an analyst to know anything beforehand about the collection they're analyzing.

Who would use this: An Analyst who is given a collection of raw or unknown information, and asked to analyze the information.

Automatic Summarization

Takes a single document, identifies the most relevant sentences, and creates an “ad hoc” summary.

Why this is better: It doesn’t paraphrase the document – the sentences are the actual content, and it doesn’t matter how long or complicated the document is.

Who would use this: An Analyst who needs a quick “snapshot” of lengthy or complicated documents.

Cross-Lingual Analysis

Analyzes documents in their native languages without translation – for search, categorization, taxonomy generation, or summarization.

Why this is better: No translation is needed – can work in the language of choice (usually English) yet analyze documents in all supported languages.

Who would use this: An Analyst who works with documents in native languages, i.e. native files or even RSS feeds from foreign sources. Cross-Lingual Analysis currently operates in 16 native languages, including Asian and Middle Eastern.

Software Developer's Kit

The Software Developers Kit for Content Analyst is intended to address the complex, often conflicting architectures that our OEM customers support by offering an architecture that is flexible and modular. Our overall architecture is modular in nature: