Learning Objects, Digital Library Research Laboratory
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Browsing Learning Objects, Digital Library Research Laboratory by Author "Chitturi, Kiran"
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- CrawlingFox, Edward A.; Khandeparker, Ashwin S. (2012-11-28)This module covers the basic concepts of Web crawling, policies, techniques and how these can be applied to Digital Libraries.
- Information Retrieval System EvaluationWei, Shiyi; Suwardiman, Victoria; Swaminathan, Anand (2012-10-03)The module introduces the evaluation in information retrieval. It focuses on the standard measurement of system effectiveness through relevance judgments.
- LucidWorks: Advanced Searching cURLMakkapati, Hemanth; Subbiah, Rajesh; Kaw, Rushi (2012-10-07)This module focuses on advanced search techniques using Apache Solr through cURL. Successful completion of this module will enable students to employ advanced search techniques based on multi-values, multi-fields, phrase queries, query term proximity, boosting, etc. Also, students will be able to sort and display returned results in various ways.
- Overview of LucidWorks Big Data SoftwareChitturi, Kiran (2012-09-16)This module introduces the basic concepts and the overview of LucidWorks Big Data software that is specifically designed for searching, discovery, and analysis of massive content sets.
- Relevance Feedback and Query ExpansionWu, Sichao; Zhang, Yao (2012-10-17)This module introduces the methods to improve the recall of information retrieval systems, mainly focuses on relevance feedback and query expansion.
- Text Classification Using MahoutAlam, Maksudul; Arifuzzaman, S. M.; Bhuiyan, Md Hasanuzzaman (2012-11-06)This module focuses on classification of text using Apache Mahout. After successful completion of this module, students will be able to explain and apply methods of classification, correctly classify a set of documents using Apache Mahout, and construct and apply workflows for text classification using Apache Mahout.
- Text Clustering Using LucidWorks and Apache MahoutChen, Liangzhe; Lin, Xiao; Wood, Andrew (2012-11-17)This module introduces algorithms and evaluation metrics for flat clustering. We focus on the usage of LucidWorks big data analysis software and Apache Mahout, an open source machine learning library in clustering of document collections with the k-means algorithm.