[hive-mrc] r650 committed - Edited wiki page Welcome through web user interface.

[hive...@googlecode.com]

Revision: 650
Author: craig....@unc.edu
Date: Mon Jun 11 18:10:23 2012
Log: Edited wiki page Welcome through web user interface.
http://code.google.com/p/hive-mrc/source/detail?r=650

Modified:
/wiki/Welcome.wiki

=======================================
--- /wiki/Welcome.wiki Mon Feb 28 07:36:54 2011
+++ /wiki/Welcome.wiki Mon Jun 11 18:10:23 2012
@@ -2,19 +2,14 @@

= What is HIVE? =

-HIVE is an automatic metadata generation approach that dynamically
integrates discipline-specific controlled vocabularies encoded with the
Simple Knowledge Organisation System (SKOS), a World Wide Web Consortium
(W3C) standard. HIVE will assist content creators and information
professionals with subject cataloging and will provide a solution to the
traditional controlled vocabulary problems of cost, interoperability, and
usability.
-
-HIVE functions:
- * Conversion of vocabularies to SKOS
- * Rich internet application (RIA) for browsing and searching multiple
SKOS vocabularies
- * Java API and REST application interfaces for programmatic access to
multiple SKOS vocabularies
- * Support Natural language and SPARQL-based queries
- * Automatic keyphrase indexing using multiple SKOS vocabularies. HIVE
supports two indexers:
- * KEA++ indexer
- * Basic Lucene indexer
-
-
-Learn more:
- * [AboutHiveCore About HIVE Core]
- * [AboutHiveWeb About HIVE Web]
- * [AboutKEA About KEA]
+HIVE is a framework and service for the integration of multiple controlled
vocabularies and thesauri using Simple Knowledge Organization (SKOS) format.
+
+HIVE features can be used in three ways:
+ * [AboutHiveWeb HIVE Web]: GWT-based web application
+ * [AboutHiveCore Core API]: Java SE API for programmatic access
+ * [AboutHiveRestService REST Service]: REST-based service for
programmatic access
+
+HIVE supports the following functions:
+ * Conversion of various vocabularies to SKOS
+ * Browsing and searching SKOS vocabularies (Concept Browser)
+ * Automatic controlled indexing using [http://www.nzdl.org/Kea/ KEA++],
[https://code.google.com/p/maui-indexer/ Maui], and simple Lucene-based
indexers.