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Data Warehousing and Data Mining




                    notes          The response time of a query using the Full Scan technique:
                                                        CostModel(m) = (m * att) + (m * itime(fs))

                                   Where,
                                             m = Total number of tuples in the relation
                                            att = Access time per tuple
                                          itime = Instruction time of an algorithm
                                             fs = Full scan algorithm

                                   Since the full scan technique is unaffected by the found set of department relation and the number
                                   of selective attributes. Therefore;
                                   Response time of a query = (10,000 * 0.1) + (10,000 * 0.05) = 1,500 sec.
                                   The response time of a query remains constant. The average response time for 10% to 100% found
                                   set is 1,500 sec.

                                   11.4.4 scanning with index techniques

                                   To access all the tuples in a relation is very costly when there are only small found sets. Since
                                   fetching data in the index level is normally 1/10 smaller than table level, therefore, an indexing
                                   technique is introduced. For example, to fetch data from the table level is 0.1 sec. and to fetch
                                   data from index level is 0.01 sec. Query processing will first process data in the index level and
                                   then only will it fetches data from the table level. In the following subsections, we discuss the
                                   efficiencies of the RID index technique and BitMap Index Technique in query processing.




                                      Task     A database has four transactions.  Let min sup = 60% and min_conf = 80%

                                          Tid                   date                 intms_bought
                                          T100                  10/15/99             {K,A,D,B}
                                          T200                  10/15/99             {D,A,C,E,B}
                                          T300                  10/19/99             {C,A,B,E,}
                                          T400                  10/22/99             {B,A,D}

                                     1.   Find all frequent item sets using FP_growth and Apriori techniques. Compare the
                                          efficiency of the two mining processes.
                                     2.   List all the strong association rules (with support and confidence c) matching the
                                          following meta rule, where X is a variable representing customers and item i denotes
                                          variable representing items (eg “A”,”B” etc.)

                                     Transaction, buys (X item ) buys (X, item )=>(X, item ) [s,c]
                                                                      2
                                                                               3
                                                          1
                                   11.4.5 riD index technique

                                   The  RID  index  technique  is  one  of  the  traditional  index  techniques  used  in  the  Transaction
                                   Processing  System  (TPS).  The  RID  index  creates  a  list  of  record  identification  which  acts  as
                                   pointers to records in the table. The total time that is required to process a query is access time of
                                   index level and access time of selective table level.





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