Akademik Dersler - İçerik

0 : Does not support 1 : Low-level support 2 : Mid-level support 3 : Top level support

Learning Outcomes	1	2	3	4	5	6	7	8	9	10	11	12
Knows how to process queries that have spelling errors and other imprecise matches to the vocabulary in the document collection being searched.	-	-	-	-	-	-	-	-	-	-	-	-
Describes the development of term weighting and the computation of scores using the idea of a list of documents that are rank-ordered for a query.	-	-	-	-	-	-	-	-	-	-	-	-
Compares the relative performances of different systems on benchmark document collections and queries.	-	-	-	-	-	-	-	-	-	-	-	-
Develops traditional probabilistic IR, which provides a framework for computing the probability of relevance of a document, given a set of query terms.	-	-	-	-	-	-	-	-	-	-	-	-
Develops software using Apache Lucene; which is a high-performance, full-featured text search engine library written entirely in Java.	-	-	-	-	-	-	-	-	-	-	-	-