Reasoning with fuzzy ontologies

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Reasoning with fuzzy ontologies

Constructing a domain specific ontology is tedious commitment. Through reasoner the created ontology can be evaluated. The reasoner checks the consistency of the classes and evaluates the occurrence of any obvious errors. The ontology entities are expected to be consistent with intuitions.

The ontology instance has to be minimal redundant. Thus to maintain the high quality ontology, the designed ontology should be meaningful, correct, minimally redundant, and richly axiomatised. The main objective of this paper is to create a logical entailment between the domain specific ontology and entities using fuzzy rule. This is a preview of subscription content, log in to check access. Rent this article via DeepDyve.

reasoning with fuzzy ontologies

Comput Commun — Brooke A, Wei D Architecture for automated annotation and ontology based querying of semantic web resources. Chai Y Recognition between a large number of flower species.

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Zou J, George N Evaluation of model-based interactive flower recognition. In: Proceedings of the 17th international conference on pattern recognition, vol 2, pp — Download references.Thanks for helping us catch any problems with articles on DeepDyve. We'll do our best to fix them. Check all that apply - Please note that only the first page is available if you have not selected a reading option after clicking "Read Article".

Include any more information that will help us locate the issue and fix it faster for you. A significant interest developed regarding the problem of describing databases with expressive knowledge representation techniques in recent years, so that database reasoning may be handled intelligently.

Therefore, it is possible and meaningful to investigate how to reason on fuzzy relational databases FRDBs with fuzzy ontologies. In this paper, we first propose a formal approach and an automated tool for constructing fuzzy ontologies from FRDBs, and then we study how to reason on FRDBs with constructed fuzzy ontologies. On the basis of this, we propose a formal approach that can directly transform an FRDB including its schema and data information into a fuzzy OWL ontology consisting of the fuzzy ontology structure and instance.

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Open Advanced Search.The library helps to integrate a fuzzy ontology with object-oriented programming OOP classes written in. It is a hybrid integration, i. NET class. It can be however easily modified to support any fuzzy ontology notation as well as any fuzzy reasoner.

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One way of capturing and storing knowledge in a structured and machine-interpretable way is the use of ontology engineering. Ontology includes a vocabulary of terms together with the specification of their meaning. From the explicitly declared facts, an inference mechanism allows to elicit additional implicit knowledge. Such a mechanism is implemented by means of ontology reasoners. OWL 2 is nowadays one of the most popular languages for authoring ontologies.

Fuzzy rule based ontology reasoning

It has been originally intended just for publishing semantic content of web pages, i. But eventually, it has attracted strong academic and commercial interest. Figure 1 reveals the boundary between OWL syntax and semantic layer.

It is worth to notice that there exist various concrete syntaxes that can be used to serialize and exchange OWL ontologies.

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RDF Resource Description Framework is a concept modelling approach that aims on building a collection of statements about resources in the form of subject-predicate-object expressions. As the result, the collection in fact describes a directed, labelled multi-graph.

As shown in Table 1a comparison of ontology and object modelling reveals handful of similarities. Indeed, integration of ontology with mainstream object oriented programming languages OOPLs like C or Java, suggests itself quite obviously. OWL ontology element.

Fuzzy Ontology Framework

C OOP element. Concept TBox level. Individual ABox level.

reasoning with fuzzy ontologies

Object Property role, slot Member i. Data Property data slotDatatype literal. Data type booleanintdoublestringThere are, however, also several differences, such as:. There are two types of OOP modelling. Classical ontology languages are not appropriate to deal with imprecision or vagueness in knowledge. This approach allows concrete domains datatypes to be represented by fuzzy sets. Regarding its application, fuzzy SHOIN D has been originally proposed for logic-based information retrieval in a document management system [5].

The former reasoner represents queries as a linear optimization problem, the latter one computes a rough equivalent non-fuzzy representation from a fuzzy source assuming a finite chain of degrees of truth.The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We propose to use the language OWL 2 itself the current standard ontology language to represent fuzzy ontologies.

More precisely, we use OWL 2 annotation properties to encode fuzzy ontologies. The use of annotation properties makes possible to use current OWL 2 editors e. A full description of the syntax of the fuzzy ontologies, and of the methodology to represent them, is described in a technical report available at the Documentation section.

Let us consider an example. In this section, we will provide some examples illustrating how to encode the fuzzy ontologies using our approach.

Some fuzzy ontologies are explained in a technical report available at the Documentation section. The plug-in supports you in creating Fuzzy OWL 2 ontologies, without bothering about how to write the annotations.

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The plug-in allows you also to submit queries to the fuzzyDL reasoner. Once the fuzzy ontology has been created with a conventional ontology editor, it has to be translated into the language supported by some fuzzy ontology reasoner, so that we reason with it.

For this purpose, we have developed a template code for a parser translating from OWL 2 with annotations representing fuzzy information into the language supported by some reasoner class. This general parser can be adapted to any particular fuzzy DL reasoner. As illustrative purposes, we have adapted it to the languages supported by two fuzzy DL reasoners: fuzzyDL and DeLorean. It is important to point out that similar parsers for other fuzzy DL reasoners can be obtained without difficulties.

The old package can be obtained from here. A screenshot. From the plug-in you may also query the fuzzyDL reasoner.Topic - Reasoning. The ClojureTab uses the Clojure programming language for simple programming in the Protege environment, on-the-fly debugging, and storing programs in Protege projects.

Reasoning Problems on Distributed Fuzzy Ontologies

Contains: 1. Protege API for Clojure language 3. Algorithms visual development environment. The DroolsTab uses the open source geo-information system Java library OpenMap and the open source Java RETE rule engine Drools to facilitate visual authoring of complex spatial process simulation scenarios and general rule-based authoring.

The Groovy and Clojure languages can be used for authoring auxiliary pieces of code and scripts. The distribution includes several demos of spatial simulation in the sea, air, and ground environments, including one example using Edvin Boehn's KML Framework.

Uses concept of "Scenario" for describing spatial processes and programming language Clojure for executive parts of rules and auxilliary scripts.

Includes general IDE for Clojure. Reasoning From Protege Wiki. Jump to: navigationsearch. Category : Topic. Views Page Discussion View source History. Personal tools Log in. Algernon performs forward and backward rule-based processing of frame-based knowledge bases, and efficiently stores and retrieves information in ontologies and knowledge bases. Facilitate acquisition of Protege Axiom Language PAL based constraints without having to understand the language itself.

Expert System Shell r4f-pro. Integrated Development Environment for rete4frames rule engine and expert system shell based on Protege It combines two well-known paradigms of software development: algorithms for strictly defined processes and rules for fuzzy, fragmentarily defined processes and phenomenons.

Given an OWL file, HermiT can determine whether or not the ontology is consistent, identify subsumption relationships between classes, and much more.

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HyperMod is a module extraction tool based on reachability in hypergraphs. These modules are similar to syntactic locality based modules but has the potential of being substantially smaller. Integrated development environment for visual creation and simulation of spatial processes. Individual properties contextual assertion.

Mastro DL-Lite Reasoner. Ontologies in Mastro are specified through languages belonging to the DL-Lite family of lightweight Description Logics. The ontology is connected to external relational data management or data federation systems through a mapping establishing a semantic relation between SQL queries issued over the underlying databases and elements of the ontology.

It's extremely fast and is packed with features. Ontop is an open-source Ontology Based Data Access OBDA system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. After the transformation it produces in the given path a. PSM Librarian. Supports users in building knowledge-based applications out of reusable knowledge components known as Problem-Solving Methods PSMs.

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Express constraints about a knowledge base and make logical queries about the contents of a knowledge base. Snorocket for Protege is a Java implementation of the polynomial classification algorithm described by Baader et al in Pushing the EL Envelope and packaged for use as a reasoner in Protege.Three or four maximum. Once you find yourself putting that 20-fold accumulator on, you really are on cloud cuckoo land. Bookies lose most of their money from singles.

But trebles usually offer a decent return if you really do want a higher payout. If you do find yourself desperately wanting that long-shot bet on a Saturday afternoon, do not pad out your accumulator with odds-on selections.

You're decreasing your chance of winning for next to no extra cash. This is really easy to do in tennis. It's the opening week of a Grand Slam and you see the top players are all drawn against relative unknowns. It would seem like a great idea to lump them altogether in a multiple to try and win some easy money. But this would be a mistake. It would make more sense to do some research and find an up-and-coming player who has a favourable draw and back them at a better price.

Again, once you've done enough research, you should know you're sport well enough to find better value in the hundreds of other markets the bookies offer. It is arguably a way for the bookies just to provide you with more ways to lose but you can find the good prices if you look hard enough.

They're higher than them in the league but does that mean they're a stronger team. That's for the football pages to discuss. But just a minimal amount of research shows that Jamie Vardy is the league's top scorer.

So betting on him to score anytime is as safe as bets come. While we're on the subject of the less obvious markets, if you do pick an obscure one, make sure to check the terms with the betting shop staff.

If you back your team to win both halves, you are betting on them to win the first half and the second half separately. The team must score more goals than the opposition in both halves for you to win your bet. It's a subtle difference but frustrating for punters who come looking to collect winnings when they're team was leading 2-1 at half time and won the match 2-1.

The second-half score must have been 0-0 and so the bet goes down. You might really want your team to win.But i do this to help you be scammed by bet365.

Fuzzy Ontology Representation using OWL 2

In few words my story. After few bets in one day when i try to login i saw my account blocked. I contact them and they ask selfie whith id in hand. I did this and after they asked me postal code. After one month i received this code and give this to them. I was in bank and took bank statement from atm machine. Was not enough again. They asked bank statement stamped by bank. Si i was again in bank and took bank statement stamped. And now guess what.

I asked them to send my money back because i did not win anything. If you dont believe me i can provide all my emails and chats whith them. I just hope my story will help many peoples avoid this SCAM bookmaker. My partner has been betting with them for quite awhile and they gladly take his money.

He had a half decent win on the weekend and they will NOT release HIS money. They are telling him that he needs photo ID before they will release it.

Why do they need photo ID to release his money and they don't ask for photo ID to take his money. Keeping my partners money is theft, pure and simple. They will allow him to use the money to keep betting but as it is quite a substantial amount my partner wants to withdraw it. Every person he talks to on the phone tells a different story, sounds suss to me. Stay away from this bunch of thieves!!. Avoid at all costs please why do you think this site has a low trust pilot score. Multiple threads opened and different person every time.

Robotic responses and every time asking me to answer the following Your username - Your full name- Your date of birth- The first line of your address and your postcode- Your email address registered to your account- The date and amount of your most recent deposit or withdrawal into your account or the last four digits of the payment type you have registered on your account (e.

Credit Card, Neteller account number etc)- A four-digit security number that you would like registering to your account. This should be easy to remember but not contain common sequences e.

Of which I have replied and replied. You are signed into your account and the robotic drones are asking for details all of which is on the account you are signed into. Even if the person responding was not the person answering the message the would have all the information. Also why would someone gain access to someones account to ask why a bet has not been settled.

reasoning with fuzzy ontologies


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