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Web Data Discovery and Sourcing Approaches

BizKonnect helps global companies to increase B2B sales globally. Our more successful customers are the ones who have clarity in terms of who their prospects are, have some customer base, the management has good network and they want to scale up their sales leveraging the corporate ecosystem.

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Web Data Discovery and Sourcing Approaches

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  1. Web Data Discovery and Sourcing Approaches for Text Analytics BizKonnect helps global companies to increase B2B sales globally. Our more successful customers are the ones who have clarity in terms of who their prospects are, have some customer base, the management has good network and they want to scale up their sales leveraging the corporate ecosystem. “The web data discovery and sourcing problem is multifold: ranging right from intellectual property ownership/control, volume, ethics, precision and authenticity. A knowledgebase should at the least adhere to select resources which assure a degree of credibility, authenticity, repeatability, reliability and quality. Just because something is there on the web doesn’t necessarily mean it’s easy to find. Most of the time, we know what we want but don’t know where we can find it and how we can use it.” Today, the World Wide Web has become the most wide, deep and important information source. The content available on the web can be broadly categorized in to two types: text and media (image, video and audio). Browsers and search engines make this content accessible for users who do an ad hoc search and analysis. For consistent and automated use of this data source, the information on the web needs to be converted in to a knowledgebase. However, this is a complicated proposition.Text analytics together with data discovery and sourcing can be used to convert this hugely available text data in to a knowledgebase. Text analytics is a process of deriving information from text by employing principles and techniques of analysis methodologies like natural language processing (NLP). Text is an unstructured form of data and requires human intelligence to derive meaning by reading it. The goal of the text analytics is to discover appropriate information that is possibly not directly specified and/or is hidden and needs to be derived by understanding and relating the context and other peripheral information. Natural Language Processing (or NLP) does linguistic analysis that helps the machine to read text. It uses linguistic features, dictionaries, patterns/models and ontologies to derive structured data points, relations and interpretations.

  2. Visit Us at :- http://www.bizkonnect.com/

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