• Chinnapaga Ravi
• . M Bal Raju
• . N Subhash Chandra

Distribution and uncertainty are considered as the most important design issues in database applications nowadays. A lot of ranking or top-k query processing techniques are introduced to solve the problems of communication cost and centralized processing. On the other hand, many techniques are also developed for modelling and managing uncertain databases. Although these techniques were efficient, they didn't deal with distributed data uncertainty. This paper proposes a framework that deals with both data distribution and uncertainty based on weighted high frequency items set algorithms. Within the proposed framework LMTV &GMTV algorithms are investigated for retrieving the WHFI from uncertain. The main objective of these algorithms is to reduce the n no of items which are not satisfied MTV (minimum threshold value) while extracting frequent item sets from heterogeneous local sites. Experimental results show that both proposed techniques have a great impact in reducing communication cost, pruning time & Both techniques are efficient but in different situations. The first one is efficient in the case of low number of sites while the other achieves better performance at higher number of sites

: DDB, local dB, central db. Frequent patterns, heterogeneous, uncertain data

"AN APPROACH FOR IDENTIFYING WIEGHTED HIGH FREQUENCY ITEM SETS IN UNCERTAIN DISTRIBUTED DATABASE.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.329-335, July-2018, Available :http://www.jetir.org/papers/JETIR1807053.pdf

"AN APPROACH FOR IDENTIFYING WIEGHTED HIGH FREQUENCY ITEM SETS IN UNCERTAIN DISTRIBUTED DATABASE.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp329-335, July-2018, Available at : http://www.jetir.org/papers/JETIR1807053.pdf