Difference between revisions of "X-Search"
(FORTH - XSearch description (1st draft)) |
(FORTH - XSearch description (1st draft)) |
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== Overview == | == Overview == | ||
| − | + | X-Search is a meta-search engine that reads the descritpion of an underlying search source, and is able to query that source and analyze in various ways the returned results and also exploit the availability of semantic repositories. | |
=== Key features === | === Key features === | ||
| − | ; | + | ;Provision of results clustering over any search system |
| − | : | + | :Returns textual snippets and for which there is an OpenSearch description |
| + | |||
| + | ;Provision of snippet or contents-based entity recognition | ||
| + | :Generic as well as vertical - based on predetermined entity categories and lists which can be obtained by querying SPARQL endpoints | ||
| + | |||
| + | ;Provision of gradual faceted (session-based) search | ||
| + | :Ability to gradually restrict the answer based on the selected entities and/or clusters | ||
| + | |||
| + | ;Ability to fetch and display the semantic information of an identified entity | ||
| + | :Achieved by quqeying appropriate SPARQL endpoints | ||
| − | ; | + | ;Ability to apply these services on any web page through a web browser |
| − | : | + | :Using the functionality of bookmarklets |
== Design == | == Design == | ||
Revision as of 10:38, 26 April 2012
Contents
Overview
X-Search is a meta-search engine that reads the descritpion of an underlying search source, and is able to query that source and analyze in various ways the returned results and also exploit the availability of semantic repositories.
Key features
- Provision of results clustering over any search system
- Returns textual snippets and for which there is an OpenSearch description
- Provision of snippet or contents-based entity recognition
- Generic as well as vertical - based on predetermined entity categories and lists which can be obtained by querying SPARQL endpoints
- Provision of gradual faceted (session-based) search
- Ability to gradually restrict the answer based on the selected entities and/or clusters
- Ability to fetch and display the semantic information of an identified entity
- Achieved by quqeying appropriate SPARQL endpoints
- Ability to apply these services on any web page through a web browser
- Using the functionality of bookmarklets
Design
Philosophy
This is the rationale behind the design. An example will be provided.
Architecture
The main software components forming the subsystem should be identified and roughly described. An architecture diagram has to be added here. A template for the representation of the architecture diagram will be proposed together with an opensource tool required to produce it.
Deployment
Usually, a subsystem consists of a number of number of components. This section describes the setting governing components deployment, e.g. the hardware components where software components are expected to be deployed. In particular, two deployment scenarios should be discussed, i.e. Large deployment and Small deployment if appropriate. If it not appropriate, one deployment diagram has to be produced.
Large deployment
A deployment diagram suggesting the deployment schema that maximizes scalability should be described here.
Small deployment
A deployment diagram suggesting the "minimal" deployment schema should be described here.
Use Cases
The subsystem has been conceived to support a number of use cases moreover it will be used to serve a number of scenarios. This area will collect these "success stories".
Well suited Use Cases
Describe here scenarios where the subsystem proves to outperform other approaches.
Less well suited Use Cases
Describe here scenarios where the subsystem partially satisfied the expectations.
