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Spelltower scoring algorithn12/24/2023 My first Zach Gage game was Flipflop Solitaire, and ever since then I’ve been an avid follower of his work. I’m one of those people who somehow missed out on Spelltower the first time around. Whether you’re a longtime Spelltower fan, or the game missed your radar entirely in its glory days, Spelltower+ deserves your attention. The newly launched Spelltower+ from Zach Gage and Jack Schlesinger takes the original game, modernizes it for the latest iPhone and iPad screen sizes, adds lots of new game modes, and packs several other key feature enhancements. In either case, you or your Oracle administrator must synchronize the index either with ALTER INDEX or by running ctxsrv in the background.Word game addicts, say goodbye to your family, friends, and productivity: Spelltower is back and better than ever. If DML is light, Oracle still gives fairly accurate relevance ranking. Perfect relevance ranking is obtained by executing a query right after optimizing the index. ![]() If DML is heavy, you or your Oracle administrator must optimize the index. Inverse frequency scoring also means that adding documents that contain hydrogen lowers the score for that term in the document, and adding more documents that do not contain hydrogen raises the score.īecause the scoring algorithm is based on the number of documents in the document set, inserting, updating or deleting documents in the document set is likely change the score for any given term before and after the DML. This is so even though both terms occur 5 times in the document.Įven if the relatively infrequent term hydrogen occurred 4 times in the document, and chemical occurred 5 times in the document, the score for hydrogen might still be higher, because chemical occurs so frequently in the document set (at least 5000 times). The score for hydrogen is therefore higher than that of chemical. The term hydrogen thus occurs infrequently in the document set.īecause chemical occurs so frequently in the document set, its score for the document is lower with respect to hydrogen, which is infrequent is the document set as a whole. No other document contains the term hydrogen. You have a document that contains 5 occurrences of chemical and 5 occurrences of the term hydrogen. The term chemical thus occurs frequently in the document set. You have 5000 documents dealing with chemistry in which the term chemical occurs at least once in every document. Whereas, if there were 1,000,000 documents in the set, the term would have to occur only 4 times in the document to score 100. The table illustrates that if only one document contained the query term and there were five documents in the set, the term would have to occur 20 times in the document to score 100. ![]() Occurrences of Term in Document Needed to Score 100 This table assumes that only one document in the set contains the query term. The first column shows the number of documents in the document set, and the second column shows the number of terms in the document necessary to score 100. The following table illustrates Oracle's inverse frequency scoring. For a document to score high, the query term must occur frequently in the document but infrequently in the document set as a whole. Inverse frequency scoring assumes that frequently occurring terms in a document set are "noise" terms, and so these terms are scored lower. To calculate a relevance score for a returned document in a word query, Oracle uses an inverse frequency algorithm based on Salton's formula. This appendix discusses how Oracle calculates score for word queries, which is different from the way it calculates score for ABOUT queries in English.
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