课程名称︰资讯检索 课程性质︰必修 课程教师︰唐牧群 开课学院：文学院 开课系所︰图资系 考试日期（年月日）︰2013/1/9 考试时限（分钟）：180分钟 是否需发放奖励金：是 （如未明确表示，则不予发放） 试题 : 1. With an imaginary database that contains only the following 5 document: D1: Shipment silver damaged truck D2: Delivery silver arrived silver car D3: Shipment gold damaged fire D4: Delivery gold damaged fire D5: Shipment car arrived truck (Terms in the stop word list have been grayed out). Please (1). Create an inverted file that lists all the terms in alphabetic order and each cell contains the TF(Term Frequency) weight of each terms in the documents .(5 points) (2). Calculate the DF(Document frequency) and IDF(Inverse Document Frequency) weight for each index term(simply use N/n without logarithm)(5 points). (3). Give the ranking after the user submits the query "gold silver truck" (10 points) (4). After the first iteration, the user examines the results and marks D2, D3 as relevant. Produce the new ranking using Rocchio's method where all the parameters equal 1(10 points). (5). With the same query and relevant information, calculate the new query term weight for "gold", "silver", "truck" according to Robertson and Spark Jones weighting method (hint: first you need to decide the value for "N", "R", "n", "r").(10 points) 2. Unlike data retrieval where perfect precision and recall are guaranteed, information retrieval is more of a probabilistic process where information conveyed in the retrieved documents might or might not answer user's information needs. What are the possible causes behind the uncertainty of IR (10 points)? 3. Define the following concepts and explain how they are related to one another: "specificity", "precision" and "IDF (Inverse document Frequency); "exhaustivity", "recall" and "TF(Term Frequency)".There is often a trade-off between precision and recall, is there also a trade-off between specificity and exhaustivity?(20 points)? 4. Explain the three basic models in information retrieve: Boolean, Vector space and Probabilistic (20 points). 5. Explain the rationale behind PageRank and the meaning of each component of the formula below (10 points). PR(A)=(1 - d) + d ΣPR(Ii) / C(Ii) --

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