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FINDING TOP-K PREFERABLE PRODUCTS

There are numerous applications where we wish to discover unexpected activities in a sequence of time-stamped observation data—for instance, we may want to detect inexplicable events in transactions at a website or in video of an airport tarmac. In this paper, we start with a known set A of activities (both innocuous and dangerous) that we wish to monitor. However, in addition, we wish to identify “unexplained” subsequences in an observation sequence that are poorly explained (e.g., because they may contain occurrences of activities that have never been seen or anticipated before, i.e., they are not in A). http://kaashivinfotech.com/ http://inplanttrainingchennai.com/ http://inplanttraining-in-chennai.com/ http://internshipinchennai.in/ http://inplant-training.org/ http://kernelmind.com/ http://inplanttraining-in-chennai.com/ http://inplanttrainingchennai.com/

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FINDING TOP-K PREFERABLE PRODUCTS

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  1. Optimal Price Prediction For Finding Top-k Preferable Products Using Skyline Analysis IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING OCTOBER 2012 paper FINDING TOP-K PREFERABLE PRODUCTS

  2. A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional VenkatesanPrabu .J MANAGING DIRECTOR Microsoft Web Developer Advisory Council team member and a well known Microsoft Most Valuable Professional (MVP) for the year 2008, 2009, 2010,2011,2012,2013 ,2014. LakshmiNarayanan.J GENERAL MANAGER BlackBerry Server Admin. Oracle 10g SQL Expert. Arunachalam.J Electronic Architect Human Resourse Manager

  3. Abstract • There are numerous applications where we wish to discover unexpected activities in a sequence of time-stamped observation data—for instance, we may want to detect inexplicable events in transactions at a website or in video of an airport tarmac. In this paper, we start with a known set A of activities (both innocuous and dangerous) that we wish to monitor. • However, in addition, we wish to identify “unexplained” subsequences in an observation sequence that are poorly explained (e.g., because they may contain occurrences of activities that have never been seen or anticipated before, i.e., they are not in A). • We formally define the probability that a sequence of observations is unexplained (totally or partially) w.r.t. A. We develop efficient algorithms to identify the top-k Totally and partially unexplained sequences w.r.t. A.

  4. Existing System • To find top k profitable products: A inexperienced way for this instance problem is to itemize all possible subsets of size k from the available set and then calculate the sum of the profits of each possible subset and finally choose the subset with greatest sum. • To find top k popular products: A immature way for this instance problem is similar to that of the first instance. First find all possible subsets of size k from the available set and then choose the subset with greatest number of customers

  5. Proposed System • To find top k profitable products: A dynamic programming approach is proposed, which finds an optimal solution when there are two attributes to be considered. Here we are utilizing the option of find Optimal Incremental Property Algorithm. In which, we are trying to validate/identify the quasi dominance of the products and apart from that our system will recognize the skyline checks on the available data. Based on an optimized check among the two technical jargons, the profitable products will be identified. • To find top k popular products: The adaptive pulling strategy related to the products prioritizes access among the two relations based on the observed data. The main idea behind this approach is to read the tuples from a relation only if there is possible evidence regarding the new tuples which will help and satisfy the termination condition.

  6. System Requirements • Hardware Requirements: Platform : DOTNET (VS2010) , ASP.NET Dot net framework 4.0 Database : SQL Server 2008 R2 • Software Requirements: Processor : Core 2 duo Speed : 2.2GHZ RAM : 2GB Hard Disk : 160GB

  7. Architecture Diagram

  8. Records Breaks Asia Book Of Records Tamil Nadu Of Records India Of Records MVP Awards World Record

  9. Services: A Software /Manufacturing Research Company Run By Microsoft Most Valuable Professional Inplant Training. Internship. Workshop’s. Final Year Project’s. Industrial Visit. Contact Us: +91 98406 78906,+91 90037 18877 kaashiv.info@gmail.com www.kaashivinfotech.com Shivanantha Building (Second building to Ayyappan Temple),X41, 5th Floor, 2nd avenue,Anna Nagar,Chennai-40.

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