To select the match cutoff value you should review create a Weight Histogram Table by running the match run in the determineĬutoffs mode. You can specify the comparison functions used. Record pairs that have a composite score equal to or greater than the matchĬutoff value are declared to be matches.
All pairs of recordsĪre compared, a composite score is computed for each pair of records, and Only one match cutoff value is specified. Values in columns, without you specifying the exact set of columns that This type of matching allows you to match records by comparing the Match Rule Type: Fuzzy, combined single limit To be declared a match, all match columns must be a match. If the score is greater orĮqual to the match cutoff value, the column is declared to be a match. The score returned by the column's comparison function is compared with the column's This type of matching allows you to specify the match cutoff and comparison function for each match column. The Exact type of match rule is simple, yet very powerful, particularly if you standardize your columns first. Fusion performs data matching by running a matching specification that contains one or more match rules that areįusion supports the following types of match rules:įor this type of rule, records that have equal values in the match columns are considered duplicates. Match rules define the conditions that must exist for records to be declared duplicates. Survivorship function: For a set of matched records, a survivorship function is used to determine which record's value will be used in the final merged record. Match cutoff: If the comparison of two values or records generates a score greater than or equal to the match cutoff value, the values or records are declared a match. This value is specified as a percentage ranging from 0 to 100. (See Comparison Functions.)Ĭomposite score: The composite score of comparing two records is computed as a sum of the column comparisons scores for the given columns, divided by the number of columns. Fusion provides several comparison functions that allow the implementation of fuzzy matching.
Match column: A column used in the matching process to determine if records are duplicates.Ĭomparison function: A comparison function compares a column's value in two records and determines the likelihood that the values match. Records into a single consolidated record.
Same real-world entity (duplicate records) and merging the identified You can then switch between those different bookmark toolbars easily depending on the work at hand.How Data Matching for Deduplication (One Source Matching) Worksįusion's one source matching functionality automates the process of identifying records that represent the This can be used for a very unique experience as it is possible to create multiple toolbars that have been customized for specific work situations, say school and office, research or entertainment. The first notable difference to the default bookmarking behavior in Firefox becomes apparent immediately as it is possible to display all bookmark folders, or only a specific one in a toolbar. The add-on displays a new bookmarks toolbar by default which can be hidden if it is not needed. It is an all bases covering add-on that comes with several interesting features for users who would like to have more control over their bookmarks and the way they are displayed in the web browser. The Incredible Bookmarks add-on for Firefox changes this. It is for instance not possible to check for duplicate bookmarks or dead links in the bookmarks manager, or to comfortably change the bookmarks that are displayed in one of the web browser toolbars. Firefox's bookmark management capabilities are limited.
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