• B. DEEPA SURESH
• CHANDRA SHEKAR s

A key task in integrating data from multiple Web sources is to recognize records referring to the same real world entity— the record linkage problem. This task is known to be difficult since the attribute values of an entity may be represented in different ways or even conflict with each other, e.g., different addresses for the same business. Conflicting data may also occur because of multiple correct values for the same real world entity, incomplete data, out-of-date data or erroneous data. Thus, another important task is to identify the correct attribute values of an entity—the data fusion problem. Although much work has been conducted on these problems, there is limited work on creating a uniform, standard record from a group of records corresponding to the same real-world entity. To overcome from all these problems a Record Normalization is implemented in this paper. This paper proposes a comprehensive framework for computing the normalized record and presents in-depth analysis of normalization granularity levels (e.g., record, field, and value-component) and of normalization forms (e.g., typical versus complete

Record normalization, data quality, data fusion, web data integration, deep web.

"A Computational & Unique Framework of Single and Multi-Strategy Approach for Normalization of Duplicate Records", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.674-676, March-2019, Available :http://www.jetir.org/papers/JETIR1903204.pdf

"A Computational & Unique Framework of Single and Multi-Strategy Approach for Normalization of Duplicate Records", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp674-676, March-2019, Available at : http://www.jetir.org/papers/JETIR1903204.pdf