A set of text based documents produce the following “alone, animation, best, cold, enjoy, ever, filled, film, he, horror, i, love, most, movie, night, one, outside, overrated, put, plot, really, seen, story, scary, suspense, toy, twist, unexpected, watching” If the corresponding set of text based documents consist of: D1 = I enjoy watching movies when it’s cold outside; D2 = Toy story is the best animation movie ever; D3 = Watching horror movies alone at night is really scary; D4 = He loves film filled with suspense and unexpected plot twists D5 = This is one of the most overrated movie I’ve ever seen. and if the query document Q contains key terms watching best animation movies, perform hand calculation to determine the rank of every single document above if the retrieval process is performed using BM25 approach. Please use k1 = 1.5, b = 0,75, and modify IDF equation to avoid IDF with negative values to IDF(qi)=loge(1+(N−DF(qi)+0.5)/(DF(qi)+0.5)) where N is the number of documents and DF(qi) is the number of documents that contain term qi.
A set of text based documents produce the following
“alone, animation, best, cold, enjoy, ever, filled, film, he, horror, i, love, most, movie, night, one, outside, overrated, put, plot, really, seen, story, scary, suspense, toy, twist, unexpected, watching”
If the corresponding set of text based documents consist of:
D1 = I enjoy watching movies when it’s cold outside;
D2 = Toy story is the best animation movie ever;
D3 = Watching horror movies alone at night is really scary;
D4 = He loves film filled with suspense and unexpected plot twists
D5 = This is one of the most overrated movie I’ve ever seen.
and if the query document Q contains key terms watching best animation movies, perform hand calculation to determine the rank of every single document above if the retrieval process is performed using BM25 approach. Please use k1 = 1.5, b = 0,75, and modify IDF equation to avoid IDF with negative values to IDF(qi)=loge(1+(N−DF(qi)+0.5)/(DF(qi)+0.5)) where N is the number of documents and DF(qi) is the number of documents that contain term qi.
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