The document introduces Lucene, Solr, and Nutch. It describes Lucene as a Java library for indexing and searching that is powerful and fast. It describes Solr as an HTTP-based index and search server with a web-based administration panel. It describes Nutch as Internet search engine software that includes a web crawler and is powerful for vertical search engines. It then provides instructions on installing Solr and includes an example of starting Solr, adding data to indexes, and demoing searching.
Special issue on Technology Enhanced LearningZHAO Sam
The editors invite scholarly articles on Technology Enhanced Learning (TEL) to focus on the technological
support of any pedagogical approach that utilizes technology, to be considered for a special issue of the MEEM,
which is the official publication of the IEEE Education Society Student Activities Committee (ISSN
1558-7908) whose primary objective is to facilitate the publication of interesting, useful, and informative
material on all aspects of multidisciplinary engineering education for the benefit of students and young
educators.
The document proposes an architecture for a fast diagnosis system in an ubiquitous society. The system works as follows: (1) A mobile agent detects body disorders and automatically diagnoses the patient. (2) It collects health data from the patient including medical records and environmental factors. (3) It finds an appropriate doctor to analyze the data. (4) The agent provides diagnosis results to the doctor for confirmation and treatment. (5) It orders medicine or emergency services, and summarizes causes to avoid future illness. The system aims to detect issues early, find the best doctors, and deliver healthcare conveniently to patients.
What is the Covering (Rule-based) algorithm?
Classification Rules- Straightforward
1. If-Then rule
2. Generating rules from Decision Tree
Rule-based Algorithm
1. The 1R Algorithm / Learn One Rule
2. The PRISM Algorithm
3. Other Algorithm
Application of Covering algorithm
Discussion on e/m-learning application
This document discusses various similarity measures that can be used to quantify the similarity between documents, queries, or a document and query in an information retrieval system. It describes classic measures like Dice coefficient, overlap coefficient, Jaccard coefficient, and cosine coefficient. It provides examples of calculating these measures and compares the relations between different measures. The document also discusses using term-document matrices and shows an example matrix.
Clustering: Large Databases in data miningZHAO Sam
The document discusses different approaches for clustering large databases, including divide-and-conquer, incremental, and parallel clustering. It describes three major scalable clustering algorithms: BIRCH, which incrementally clusters incoming records and organizes clusters in a tree structure; CURE, which uses a divide-and-conquer approach to partition data and cluster subsets independently; and DBSCAN, a density-based algorithm that groups together densely populated areas of points.
The document introduces Lucene, Solr, and Nutch. It describes Lucene as a Java library for indexing and searching that is powerful and fast. It describes Solr as an HTTP-based index and search server with a web-based administration panel. It describes Nutch as Internet search engine software that includes a web crawler and is powerful for vertical search engines. It then provides instructions on installing Solr and includes an example of starting Solr, adding data to indexes, and demoing searching.
Special issue on Technology Enhanced LearningZHAO Sam
The editors invite scholarly articles on Technology Enhanced Learning (TEL) to focus on the technological
support of any pedagogical approach that utilizes technology, to be considered for a special issue of the MEEM,
which is the official publication of the IEEE Education Society Student Activities Committee (ISSN
1558-7908) whose primary objective is to facilitate the publication of interesting, useful, and informative
material on all aspects of multidisciplinary engineering education for the benefit of students and young
educators.
The document proposes an architecture for a fast diagnosis system in an ubiquitous society. The system works as follows: (1) A mobile agent detects body disorders and automatically diagnoses the patient. (2) It collects health data from the patient including medical records and environmental factors. (3) It finds an appropriate doctor to analyze the data. (4) The agent provides diagnosis results to the doctor for confirmation and treatment. (5) It orders medicine or emergency services, and summarizes causes to avoid future illness. The system aims to detect issues early, find the best doctors, and deliver healthcare conveniently to patients.
What is the Covering (Rule-based) algorithm?
Classification Rules- Straightforward
1. If-Then rule
2. Generating rules from Decision Tree
Rule-based Algorithm
1. The 1R Algorithm / Learn One Rule
2. The PRISM Algorithm
3. Other Algorithm
Application of Covering algorithm
Discussion on e/m-learning application
This document discusses various similarity measures that can be used to quantify the similarity between documents, queries, or a document and query in an information retrieval system. It describes classic measures like Dice coefficient, overlap coefficient, Jaccard coefficient, and cosine coefficient. It provides examples of calculating these measures and compares the relations between different measures. The document also discusses using term-document matrices and shows an example matrix.
Clustering: Large Databases in data miningZHAO Sam
The document discusses different approaches for clustering large databases, including divide-and-conquer, incremental, and parallel clustering. It describes three major scalable clustering algorithms: BIRCH, which incrementally clusters incoming records and organizes clusters in a tree structure; CURE, which uses a divide-and-conquer approach to partition data and cluster subsets independently; and DBSCAN, a density-based algorithm that groups together densely populated areas of points.
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