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Search and Search-based Applications

Enterprise search continues to underperform but there is a demonstrated way to improve search - using text analytics to automatically or semi-automatically create metadata and add it your documents.

The KAPS Group has had extensive experience using entity extraction and auto-categorization to build faceted navigation/search applications.

Adding text analytics to search also creates the foundation for building high-performing search-based applications (Info Apps). These applications include e-Discovery, business intelligence, customer intelligence, fraud detection, resume analysis, essay evaluation - in a business context, automatic summarization, and more.

SharePoint

SharePoint has become a must-have for many organizations. Its combination of collaboration and content management is a winning combination.

BUT, despite some claims, the support for taxonomies and metadata is at best not very strong. To maximize the value of SharePoint, what is needed is good metadata and taxonomy design along with text analytics to semi-automate the development and the implementation of auto-tagging.

The KAPS Group has the expertise to aid companies with the entire process from design to the development of high quality metadata, and finally the integration of the text analytics components into search and auto-tagging in SharePoint.


  Social Media & Sentiment Analysis

Social media applications are still growing rapidly in size and importance as they enter their second generation. The essential characteristic of the second generation social media applications is the increasing sophistication of text handling capabilities. For example, without good text analytics, early sentiment analysis applications performed barely better than random chance.

The KAPS Group has developed multiple social media analysis applications in partnership with text analytics vendors and social analysis companies.

Our Deep Text approach can improve the quality and lower the cost of developing all the applications that can be built using sentiment analysis.

The Deep Text approach adds depth and intelligence to social media applications through its ability to delve into the complexity of language to disambiguate and more accurately assess the mood and content of the wildly chaotic writing often found in social media.


  Deep Text Survey

The KAPS Group has also developed a product that can be quickly and economically adapted to any survey on any subject. Using a combination of clustering and entity extraction, we can build a simple taxonomy of topics and themes found in the free text portion of the survey. We then use our taxonomy/ontology/sentiment experience supplemented by auto-categorization to quickly analyze the full set of free text input.

The output is a report that can be used as is or, as we usually recommend, it can be used as tool by your subject matter experts to semi-automate their analysis. The resulting analysis can be done both faster and better by taking advantage of the respective strengths of text analytics and human expertise.


  
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