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Question 1: (6- 4+2)Try and find a Query of the form [Query-term-1, Query-term-2] (without quotes) that,when runon Google, produces at least one result that contains only one of three terms. That is, tryto findan example where Google does not interpret a the-term query as a conjunction. (If youhavedifficulty with finding an appropriate query, try one that produces very few hits, say,fewer than20.)
Take screenshot of the first page of Google results (or more if you want to)and markeach result with 2 (both terms occur on the page), 1 (one term occurs on thepage) or0 (neither term occurs on the page)Based on this evidence, does Google interpret all queries as a Booleanconjunction?
Explain.Question 2: (16: 8+4+4)Recall and Precision are two important evaluation metrics that we use to analyze a setofunranked results. Precision and Recall metrics consider the differences between set ofdocuments retrieved for given query and the set of documents that are relevant to theuser’sneed.A) Compute Recall, Precision and [email protected] for the following retrieval againstQueriesQ1, Q2 and Q3
1,14,17,23, 24, 33,54, 55, 59,74,101,103
2,5,7,23, 33,50, 55, 59, 77,98, 99,101, 103, 110,120
14,19, 25, 27,30,39, 42, 63, 769,790,1563
14, 21, 25, 26,27, 38, 42, 63, 569,769, 790, 1565, 1589
8, 11,32,54,67,69,78, 79,91,99,111,122
11, 13, 17, 19, 21, 32,77,79,99,102,111,122
4,26, 38, 63, 569, 769, 790,1565, 1589
14, 21, 25, 26,27, 38,63, 88, 769,790,
B) Recall and Precision are often discussed together as their focus is on complementaryinformation. If precision is important, the we don’t not want to see any non-relevantdocuments. That is, whatever is retrieved, should be relevant. If recall is important, wewant to see all the relevant documents, even if it requires sifting through somenonrelevant ones. Provide and Justify two information-seeking tasks where precisionmay beconsiderably more important than recall. Similarly, Provide and Justify twoinformationseeking tasks where recall may be more important than precision. [Don’tforget to justifyyour choices: Justification will be graded, not the particular choices].C) The trade-off between Recall and Precision may be user-specific i.e. some users maybeinterested in precision than recall and vice versa. How the search engine try to guesswithout asking, whether user cares more about precision than recall, or vice versa?Think of different ways, users interact with a search engine and be creative!3Question 3: (6: 3×3)(a) Consider, we have three collections C1, C2, and C3 that have 500, 15,000 and300,000documents respectively. We have added All documents in C1, to C2 and C3. Whichcollection is likely to have more new terms added to its vocabulary (C1, C2 or C3) andwhy? [Heaps’ Law](b) Calculate the tf-idf for below documents.a. D1: Sweets Potatoes are Sweetb. D2: Sweet Oranges are sour and Sweetc. D3: I have sweet Apple, Sweet Orange, Sweet PotatoesQuestion 4: (10-5×2)
(houses OR for OR sale OR in OR Geelong OR Melbourne) (houses AND for AND sale AND in AND Geelong OR Melbourne)Suppose these are issued to a search engine that uses the ranked Boolean retrievalmodel.Assume, for simplicity, only four documents in the collection (with document ids 1-4).Answer the following questions. The above table gives the number of times each querytermoccurs in each document.
Compute the document scores and the ranking associated with the query(houses ORfor OR sale OR in OR Geelong OR Melbourne).How is the ranking produced probably sub-optimal and why does thishappen?
(iii) Compute the document scores and the ranking associated with the query (housesANDfor AND sale AND in AND Geelong OR Melbourne).(iv) How is the ranking produced probably sub-optimal and why does this happen?(v) How would you extend the Boolean retrieval model to handle AND NOT constraints(e.g., houses AND NOT Geelong)? Your proposed solution should give a higher scoreto documents that contain fewer occurrences of the term to the right of the AND NOT(e.g., Geelong). Please be as mathematical as possible. In other words, saying: “I wouldreduce the score for documents that contain the word to the right of AND NOT.” is toovague.(vi) Using the index, what would be the Boolean retrieval model scores given todocuments1-4 by your proposed scoring method for the query “houses AND NOT Geelong”?Question 5: (12-4×3)Doc1: A book is considered a good book that makes the reader feels better.Doc2: I love reading good books to feel better.Doc3: One can feel better after reading Tom’s recent book.4Query-1: I love books that are goodQuery -2: reading good books make you feel betterStop Word Dictionary=[is, can, after, a, to, I, the, about, that]
Explain the similarity scores of both Query -1 and Query -2 using TF-IDF.How would the result change if TF-IDF is used instead of TF as Query?What do prefer using TF or TF-IDF as Query (Support your claim using Fscore).
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