Excel 2013 Bible by John Walkenbach

By John Walkenbach

Excel at Excel with the aid of this bestselling spreadsheet guide

John Walkenbach's identify is synonymous with excellence in laptop books that decipher the complexities of Microsoft Excel. referred to as "Mr. Spreadsheet," Walkenbach indicates you ways to maximise the facility of Excel 2013 whereas bringing you up to the mark at the newest positive aspects. This perennial bestseller is totally up to date to hide the entire new positive factors of Excel 2013, together with tips to navigate the consumer interface, reap the benefits of quite a few dossier codecs, grasp formulation, research facts with PivotTables, and more.

Whether you're an Excel newbie who's trying to get extra savvy or a complicated consumer seeking to develop into an influence person, this most recent variation will give you complete insurance in addition to priceless information, methods, and strategies that you just won't locate anyplace else. stocks the precious perception of Excel guru and bestselling writer "Mr. Spreadsheet" John Walkenbach as he courses you thru each element of Excel 2013 offers crucial insurance of all of the most up-to-date positive aspects of Excel 2013 offers fabric in a transparent, concise, logical structure that's perfect for all degrees of Excel adventure contains a site that incorporates downloadable templates and worksheets from the book

Chart your route to brilliant formulation and stellar spreadsheets with "Excel 2013 Bible"!

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Then, as a result of a query evaluation, a fuzzy set of documents is retrieved in which the RSV is the membership value. To ren der the Boolean query language more user friendly and less limited in its expressiveness, some models have been defined which extend the atomic selection criteria by introducing query term weights [2,3,11,21]. An example of weighted query is the following: < t 1 , Wl > AND « t 2 , W2 > OR < t3,W3 » in which t 1, t 2 , t 3, are "Search terms and W1,W2,W3 E [0,1] are numeric weights.

About k: this is a soft interpretation of the quantifier at least k in which the k value is not interpreted as a crisp threshold, but as a fuzzy one. This means that the user is fully satisfied if k or more conditions are satisfied, but she/he gets a certain degree of satisfaction even if k -1, k2, . , 1 criteria are satisfied. This quantifier is defined by a weighting vector Waboutk in which Wi = i/ 2:7=1 j for i:::; k, and Wi = 0 for i > k. • most of it is defined as a synonym of at least ~n in which n is the total number of selection criteria.

Since it is not possible to have a single definition for the soft constraint Ilw that preserves the relative importance semantics independently of the connectors in the query, two distinct definitions of Ilw have been proposed, depending on the aggregation operators in the query [3], thus giving up the separability property [13,29]. Two alternative definitions have been proposed for conjunctive and disjunctive queries [2,30]. The first proposal [2] is the following: Ilw(F(d, t)) = w· F(d, t) for disjunctive queries Ilw(F(d, t)) = max(l, F(d, t)/w) for conjunctive queries (14) (15) The second proposal [30] is the following: Ilw(F(d, t)) = min[w, F(d, t)] for disjunctive queries Ilw(F(d, t)) = max[(l- w), F(d, t)] for conjunctive queries (16) (17) Notice that definitions (15) and (17) are the fuzzy implications of Goguen and Dienes respectively.

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