Watson Explorer Analytical Components 1

Introduction:

IBM Watson Explorer Analytical Components(AC) which is part of the IBM Watson Explorer Advanced Edition gives organizations the ability to access and analyze 

unstructured information that can be found both inside and outside the organization.Using sophisticated natural language algorithms, this solution can deliver

new business insight from virtually any type of content in any format including both text and data. It extracts key informaiton, then sorts filters and categorizes this

information to present the relevant content in context to the business user.

Cotent Analytics is tool for reporting statistics and for obtaining actionable insights. Actionable insights is a key concept that refers to insight into data that leads

to action. Cotent Analytics brings the power of business intelligence to all of your enterprise information,not just your structured information. The result helps you

achieve the most value from all your data, regardless of its structure.

Solution:

The biggest benefit that a content analytics solution provides is the ability to use a computer to analyze massive amounts of unstructured count in such a way

as to discover the "why" to business scenarios. Traditional business intelligence ,analyzing structured data such as volume of calls, average length of call,

amount of sales increase or decrease,is very good at describing "what" is happening. What content analytics can do is analyze the additional unstructured or

textual data associated with those events and help you find out "why".

Content Analytics delivers new business understanding and visibility from the content and context of textual information. For example, you can identify patterns,view trends and deviations over time,and reveal unusual correlations or anomalies.

Key Concepts:

Unstructured and structured content:is information that is generally recorded in a natural language as free text. The text contains all of the complexities and ambiguities of
the language that is being used. It is easily understood by a human reader but difficult to process by a computer program.

Text analytics: is a general term that refers to the automated techniques of converting textual data into structured data. A program that reads text and extracts person names is considered a text analytic.

Data mining: is the process of identifying patterns in your data that might be used to answer a business problem, question, or concern. Data mining is a natural part of discovery.
Keywords: As the term implies, keywords are usually words and phrases that are extracted from textual content. However, they can also be obtained from structured fields such as date or numeric fields.
14 IBM Watson Content Analytics: Discovering Actionable Insight from Your Content of discovery

Collections:A single content analytics or enterprise search collection represents the entire group of documents that are available to an application for search and analysis.

Facets:represent the different aspects or dimensions of your document corpus.They are a crucial mechanism for navigating and analyzing your content with the content analytics miner.

Frequency:Frequency counts in Content Analytics represent the total number of documents that contribute to a particular keyword.

Correlation:is a measure of how strongly a facet value is related (correlated) to the current query or selection criteria. In a facet pair, it indicates how two facets are correlated to each other. It is used to better gauge the relevance of a particular keyword as it compares to other data in your document corpus.

Deviation:Deviation measures the average change in a facet over time. It is a weighted,moving average.