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Content analytics tools look to be the next refinement in extracting the precise information required from data searches. Sue Feldman of IDC describes content analysis as "information intelligence" that uses "a set of language analysis processes that mimic our ability to find out the what, who, when and where of a document."
By way of explanation she says that the use of these new technologies "mirror the human process of finding underlying meaning by using clues in the grammar, syntax and superficial meaning. Once we have determined this underlying meaning, we can pull together similar ideas, even if they are expressed differently. For instance, we know that 'hypertension' and 'high blood pressure' mean the same thing."
Text analysis is now considered as just one aspect of content analysis which can also handle graphics, audio and video content - for example, converting an audio file into text and then analysing its content to extract the key content. Rita Knox of Gartner has suggested the following core uses for content analytics: "identifying high-priority clients, interpreting competitors' activities, understanding consumer responses to a new product, detecting fraud and more." She also sees its key benefits as being time savings, standardisation of data for evaluation and the performing of analysis from a neutral viewpoint unaffected by personal preferences or bias.
A number of major content management vendors are now offering these additional tools and, by way of an example, IBM recently demonstrated an analysis of a US transportation database to extract information that could point to vehicle quality issues, including covering free text comments made by drivers when reporting incidents. Another example might be the call centre which could analyse conversations for early identification of issues within the customer base.
More at: http://www.kmworld.com/Articles/Editorial/Feature/Beyond-text-analytics-53100.aspx |
