Spring 2008
Contains some of the presentations and information relating to the LINC seminars that took place in Spring 2008.
-
Ontology and Semantic Web Series
- A set of presentations and reference materials about Ontology and Semantic Web, organized by Dr. Vijay Raghavan with help of Ms. Elshaimaa Ali
-
Spatial Databases and Indexing
- by Murat Seckin Ayhan
-
Group Seminar: Header T-tree, A Main Memory Database Index
(ACTR 116, from
Apr 25, 2008 09:00 AM to
Apr 25, 2008 10:30 AM)
- by Sandeep Uda Abstract: Memory resident database systems (MMDB's) store their data in main physical memory and provide very high-speed access. There are many index structures proposed which are suitable for MMDBs. T-tree has been widely accepted as a promising index structure for main memory databases. It is a balanced tree that evolved from AVL and B-trees, and a binary tree with many elements in a node. All the basic operations like insertion, deletion, update, searching single-value query and searching range queries are discussed along with their advantages and disadvantages and a new index structure is proposed which is a variation of T-tree, will be discussed with examples.
-
Group Seminar: Introduction to two named entity extraction technics for biomedical literatures
(ACTR 116, from
May 02, 2008 09:00 AM to
May 02, 2008 09:55 AM)
- Biomedical information is growing explosively, new and useful results are appearing daily in research publications. To enable data mining and knowledge discovery from such documents, this data must be made available in a structured format. However, it is difficult to have human curators extract all of the information. Therefore, named entity recognition (the task of identifying words and phrases in free text that belong to certain classes of interest) is an important first step for many of these larger information management goals. In this study, three methods that are wildly used will be introduced along with some research papers.
-
Introduction to TREC and WT-10G
- by Bhattacharya Aditi A report about general overview regarding the text retrieval conference (TREC) and the WT10G dataset.
