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Document Annotation for Effective Structured Data Information Retrieval

Priyanka Channe, Bhagyashree Dhakulkar

Abstract


Online data sharing applications provide a way to share information between users. There are many application domains in which users create and share the textual information about their products, services. This textual information contains more structured information merged into unstructured information.  A User who wants to retrieve this structured, shared information, uses information retrieval algorithms which are inaccurate and expensive when text does not contain any example of targeted information. This data annotation is very important to facilitate finding subsequent information from shared data. In this paper, a framework is represented through which user can insert metadata during insertion time, so that identifying the data will be easy using a novel algorithm is presented that identify the metadata that really exist in documents by using content and query value and probabilistic method computation. Additionally, devise propose algorithms that mapping attribute-value to manually generated schemas for product data. Finally touch of collaborative filtering is given using which user gets recent or more related information about any event.  


Keywords


Attribute Suggestion, Collaborative Filtering, Document Annotation, Mapping Attribute-Value.

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References


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