This application use the concept of semantic technology to provide natural language search, give user more aggregated search result from the meaning not just by the keyword. Power Set can also makes a "Semantic connections" to create large database or semantic database. Power Set application is not made for racing with Google, but they are on a quest for better web communication and engagement. Both trying to let the system to be able to understand and handle data universally. Power Set search technology is now developing under Powerlabs program to differentiate Power Set from other search endeavors.
วันศุกร์ที่ 4 มีนาคม พ.ศ. 2554
Power Set : Natural Language Search
This application use the concept of semantic technology to provide natural language search, give user more aggregated search result from the meaning not just by the keyword. Power Set can also makes a "Semantic connections" to create large database or semantic database. Power Set application is not made for racing with Google, but they are on a quest for better web communication and engagement. Both trying to let the system to be able to understand and handle data universally. Power Set search technology is now developing under Powerlabs program to differentiate Power Set from other search endeavors.
วันจันทร์ที่ 28 กุมภาพันธ์ พ.ศ. 2554
Semantic Web Application

วันเสาร์ที่ 19 กุมภาพันธ์ พ.ศ. 2554
Oracle Semantic Technology
Oracle Database enables you to store semantic data and ontology, to query semantic data and to perform ontology-assisted query of enterprise relational data, and to use supplied or user-defined inferencing to expand the power of querying on semantic data. Next, let's see how these capabilities interact.
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| Oracle Semantic Capabilities |
Semantic Data Storage in Oracle
As you have known about Oracle, it offers a robust, scalable, secure platform to store RDF and OWL data. It allows efficient storage, loading and querying of semantic data. Queries are enhanced by adding relationships or ontologies that we have discussed already to data and evaluated on the basis of semantics.
Data storage is in the form of RDF triples which are Subject, Predicate, Object. The triples stored in the semantic data store are modeled as a graphed structure. All the data is stored in a single central schema allowing access to users for loading and querying data.
The Subject and Object are modeled as nodes, while the Predicates are denoted by links in the graphed structure. Nodes are stored and efficiently reused when required. An RDF triple in the semantic store has a subject or start node, predicate or relationship, object or end node, which comprises a link. A new link is created on inserting a new triple and nodes are reused if similar nodes already exists.
วันจันทร์ที่ 14 กุมภาพันธ์ พ.ศ. 2554
Epik:The Internet is evolving
4. Domain are financial instrument
วันพฤหัสบดีที่ 3 กุมภาพันธ์ พ.ศ. 2554
What is Artificial Intelligence (AI) ???

1. AI is a system that is able to conceive as a human, making decision, resolve problems, and learning.
2. AI is system that acts like a human. So, how could it been called act like a human? Alan Turing offer Turing Test in 1950 Which test acuity of AI as follows
- Natural language processing ( be able to communicate in English )
- Knowledge representation ( be able to recognize perception )
- Automated reasoning ( use information that recognize to solve the problem )
- Machine Learning ( be able to learn and adjustment )
- Computer Vision ( be able to see(visible) )
- Robotics ( changeover and be able to transfer object )
3. AI is a system that uses logic.
4. AI is a system that performs reasonably. ( rational agent )
References: Artificial Intelligence A Modern Approach, Stuart J. Russell and Peter Norvig.
วันพุธที่ 26 มกราคม พ.ศ. 2554
Ontology Dimensions Map
Before we talk about structure of ontology I would like to present an Ontology dimensions map.This diagram can serve to depict and talk about the dimensions as well as give you some understanding of the implications of metrics applied to them
It is a Template about ontologies rather than a conceptual model

Please limit interpretation of the "dimension map" to the following semantics :
- Blue ovals - There are two "nodes" related to "ontology" - essentially depicting the "what?" and the "whose?" of the ontology
- Green and lilac ovals, (over a line connecting two nodes) - There are then a series of "named arcs" or relationships/associations between nodes that depict or say something about, have or establish some relationship between two nodes - the green ones use verbs, while the lilac ones use nouns for no reason other than the fact that we didn't have time to go further: the green arcs could equally be named "formalization", "expression" and "structure"
- Red ovals, (with an unnamed directed arc pointing to a node) - There are some nodes that say something further about another node, whether it is to qualify, explain, scope or otherwise constrain
- Yellow ovals, (with an unnamed non-directed arc connecting with a node) - Some nodes have an "is" or an "is a" relationship with another node
- Finally, the nodes and arcs on the left cover, we believe the issues relating to semantic dimensions, while those on the right cover the pragmatic dimensions
I hope that this template maybe useful for you to understand more about the ontology and easy to understand the structure of it.
วันอาทิตย์ที่ 23 มกราคม พ.ศ. 2554
Example OWL
Ontology Language or Web Ontology Language (OWL)
OWL has been designed to meet this need for a Web Ontology Language OWL is part of the growing stack of W3C recommendations related to the Semantic Web.
OWL is spec started from the W3C for increase the efficiency of searching in the Internet. For example if people want to search information on the internet by giving the condition.
"Tell me what wines I should buy to serve with each course of the following menu. And, by the way, I don't like Sauternes."
Currently, there’s no tool to search any data from the internet to get the results from the above requirements exactly.
However, OWL have occasion to make agent for search query data from above.
Example OWL
credit: http://www.w3.org/TR/owl-features/
http://www.w3.org/TR/owl-guide/
วันศุกร์ที่ 21 มกราคม พ.ศ. 2554
Ontology, Web Ontology Language and Semantic web
1. Enable the movement from concept to concept in the ontology structure
2. Know the meaning or concept that we are trying to specify
3. Matching the concept, which mean that even we specify the different things, we can still match them to the same idea such as sad or sorrow, they both referring to the concept of unpleasant state of mind.
4.Disambiguation by nature of the matching and analysis of concepts and instances
5.Reasoning, which is the ability to use the structure to answer the question of relatedness; this benefit is closely related to artificial intelligent or AI and it's not expressed in standard ontology.
From the relationship structure on an ontology, they are good vehicles that lead to linkages and relatedness. the most popular use of ontologies now is Semantic search. The relationship is powerful and empower websites to organize information. One concept can related to another through a richness of vocabulary(with meaning). The use of ontologies as integration frameworks is resulting in valuable searching.
The next article will talk more about ontologies and their structures.
วันศุกร์ที่ 7 มกราคม พ.ศ. 2554
Semantic web and business-related implementation
So, the next is briefly introduction about the Semantic web to describe what is it and how does it works.
What is semantic web?
Semantic web is a technology for websites that help storing data, presenting as long as analyze and arrange each data into hierachy form, so we can know how each data will relate to another in different level . The purpose of these features is to replace the problem that we call "Information overload" from the Hypermedia web, for instance, when we search something on the website, there may have many data thats are not related to what we want, because machines cannot understand the real meaning of that word, so it cannot process and display the result we don't want it, that could waste the times and resources.
Then the Semantic web is developed to solve this kind of problem by provide a common data framework that allows us to reuse or share it across the applications or communities by that machine can understand each element of data, the example feature from Semantic web that can tell the level of relationships is "Ontology"




