Name
Abstract | ||
|---|---|---|
Recently we proposed a new context-based information retrieval system that has better retrieval effectiveness than the traditional key-word systems. In this system, each document is assigned context(s) based on the type of information. This paper presents context categories for documents in computing and information technology domain and offers a new methodology for assigning context to documents in a collection. This methodology showed promising results and the inter-assigner consistency quite comparable to the results reported in literature. The comparative evaluation of context-based information retrieval system with a baseline information retrieval system showed promising results. |
Year | Venue | Keywords |
|---|---|---|
2004 | ISICT | baseline information retrieval system,new methodology,new context-based information retrieval,better retrieval effectiveness,context-based information retrieval system,improving information retrieval effectiveness,traditional key-word system,information technology domain,context category,promising result,assigning context,information technology,information retrieval,information retrieval system |
Field | DocType | ISBN |
Cognitive models of information retrieval,Human–computer information retrieval,Information retrieval,Information technology,Data retrieval,Computer science,Relevance (information retrieval),Vector space model,Adversarial information retrieval | Conference | 1-59593-170-8 |
Citations | PageRank | References |
5 | 0.48 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vivek Chanana | 1 | 19 | 1.17 |
| Athula Ginige | 2 | 534 | 68.42 |
| San Murugesan | 3 | 523 | 56.48 |