Towards Controlled Natural Language for Semantic Annotation

Author(s):  
Brian Davis ◽  
Pradeep Dantuluri ◽  
Siegfried Handschuh ◽  
Hamish Cunningham

Richly interlinked metadata constitute the foundation of the Semantic Web. Manual semantic annotation is a labor intensive task requiring training in formal ontological descriptions for the otherwise non-expert user. Although automatic annotation tools attempt to ease this knowledge acquisition barrier, their development often requires access to specialists in Natural Language Processing (NLP). This challenges researchers to develop user-friendly annotation environments. Controlled Natural Languages (CNLs) offer an incentive to the novice user to annotate, while simultaneously authoring his/her respective documents in a user-friendly manner. CNLs have been successfully applied to ontology authoring, but little research has focused on their application to semantic annotation. This paper describes two novel approaches to semantic annotation, which permit non-expert users to simultaneously author and annotate meeting minutes using CNL. Finally, this work provides empirical evidence that for certain scenarios applying CNLs for semantic annotation can be more user friendly than a standard manual semantic annotation tool.

Author(s):  
Brian Davis ◽  
Pradeep Dantuluri ◽  
Siegfried Handschuh ◽  
Hamish Cunningham

Richly interlinked metadata constitute the foundation of the Semantic Web. Manual semantic annotation is a labor intensive task requiring training in formal ontological descriptions for the otherwise non-expert user. Although automatic annotation tools attempt to ease this knowledge acquisition barrier, their development often requires access to specialists in Natural Language Processing (NLP). This challenges researchers to develop user-friendly annotation environments. Controlled Natural Languages (CNLs) offer an incentive to the novice user to annotate, while simultaneously authoring his/her respective documents in a user-friendly manner. CNLs have been successfully applied to ontology authoring, but little research has focused on their application to semantic annotation. This paper describes two novel approaches to semantic annotation, which permit non-expert users to simultaneously author and annotate meeting minutes using CNL. Finally, this work provides empirical evidence that for certain scenarios applying CNLs for semantic annotation can be more user friendly than a standard manual semantic annotation tool.


Traditional encryption systems and techniques have always been vulnerable to brute force cyber-attacks. This is due to bytes encoding of characters utf8 also known as ASCII characters. Therefore, an opponent who intercepts a cipher text and attempts to decrypt the signal by applying brute force with a faulty pass key can detect some of the decrypted signals by employing a mixture of symbols that are not uniformly dispersed and contain no meaningful significance. Honey encoding technique is suggested to curb this classical authentication weakness by developing cipher-texts that provide correct and evenly dispersed but untrue plaintexts after decryption with a false key. This technique is only suitable for passkeys and PINs. Its adjustment in order to promote the encoding of the texts of natural languages such as electronic mails, records generated by man, still remained an open-end drawback. Prevailing proposed schemes to expand the encryption of natural language messages schedule exposes fragments of the plaintext embedded with coded data, thus they are more prone to cipher text attacks. In this paper, amending honey encoded system is proposed to promote natural language message encryption. The main aim was to create a framework that would encrypt a signal fully in binary form. As an end result, most binary strings semantically generate the right texts to trick an opponent who tries to decipher an error key in the cipher text. The security of the suggested system is assessed..


2010 ◽  
Vol 1 (3) ◽  
pp. 1-19 ◽  
Author(s):  
Weisen Guo ◽  
Steven B. Kraines

To promote global knowledge sharing, one should solve the problem that knowledge representation in diverse natural languages restricts knowledge sharing effectively. Traditional knowledge sharing models are based on natural language processing (NLP) technologies. The ambiguity of natural language is a problem for NLP; however, semantic web technologies can circumvent the problem by enabling human authors to specify meaning in a computer-interpretable form. In this paper, the authors propose a cross-language semantic model (SEMCL) for knowledge sharing, which uses semantic web technologies to provide a potential solution to the problem of ambiguity. Also, this model can match knowledge descriptions in diverse languages. First, the methods used to support searches at the semantic predicate level are given, and the authors present a cross-language approach. Finally, an implementation of the model for the general engineering domain is discussed, and a scenario describing how the model implementation handles semantic cross-language knowledge sharing is given.


Author(s):  
Mohammad Hasibul Haque ◽  
Md Fokhray Hossain ◽  
ANM Fauzul Hossain

The modern web contents are mostly written in English and developing a system with the facility of translating web pages from English to Bangla that can aid the massive number of people of Bangladesh. It is very important to introduce Natural Language Processing (NLP) and is required to developing a solution of web translator. It is a technique that deals with understanding natural languages and natural language generation. It is really a challenging job to building a Web Translator with 100% efficiency and our proposed Web Translator basically uses Machine Translator as its mother concern. This paper represents an optimal way for English to Bangla machine and the Web translation & translation methods are used by translator. Naturally there are three stages for MT but here we propose a translation system which includes 4 stages, such as, POS tagging, Generating parse tree, Transfer English parse tree to Bengali parse tree and Translate English to Bangla and apply AI. An innovation initiative has scope of being upgraded in future and hopefully this work will assist to develop more improved English to Bangla Web Translator. Keywords: Machine Translator, Web Translator, POS Tagging, Parsing, HTML Parsing, Verb Mapping DOI: 10.3329/diujst.v5i1.4382 Daffodil International University Journal of Science and Technology Vol.5(1) 2010 pp.53-61


Author(s):  
Brian Davis ◽  
Pradeep Varma ◽  
Siegfried Handschuh ◽  
Laura Dragan ◽  
Hamish Cunningham

Author(s):  
L.A. Zadeh

<p>I feel honored by the dedication of the Special Issue of IJCCC to me. I should like to express my deep appreciation to the distinguished Co-Editors and my good friends, Professors Balas, Dzitac and Teodorescu, and to distinguished contributors, for honoring me. The subjects which are addressed in the Special Issue are on the frontiers of fuzzy logic.<br /> <br /> The Foreword gives me an opportunity to share with the readers of the Journal my recent thoughts regarding a subject which I have been pondering about for many years - fuzzy logic and natural languages. The first step toward linking fuzzy logic and natural languages was my 1973 paper," Outline of a New Approach to the Analysis of Complex Systems and Decision Processes." Two key concepts were introduced in that paper. First, the concept of a linguistic variable - a variable which takes words as values; and second, the concept of a fuzzy if- then rule - a rule in which the antecedent and consequent involve linguistic variables. Today, close to forty years later, these concepts are widely used in most applications of fuzzy logic.<br /> <br /> The second step was my 1978 paper, "PRUF - a Meaning Representation Language for Natural Languages." This paper laid the foundation for a series of papers in the eighties in which a fairly complete theory of fuzzy - logic-based semantics of natural languages was developed. My theory did not attract many followers either within the fuzzy logic community or within the linguistics and philosophy of languages communities. There is a reason. The fuzzy logic community is largely a community of engineers, computer scientists and mathematicians - a community which has always shied away from semantics of natural languages. Symmetrically, the linguistics and philosophy of languages communities have shied away from fuzzy logic.<br /> <br /> In the early nineties, a thought that began to crystallize in my mind was that in most of the applications of fuzzy logic linguistic concepts play an important, if not very visible role. It is this thought that motivated the concept of Computing with Words (CW or CWW), introduced in my 1996 paper "Fuzzy Logic = Computing with Words." In essence, Computing with Words is a system of computation in which the objects of computation are words, phrases and propositions drawn from a natural language. The same can be said about Natural Language Processing (NLP.) In fact, CW and NLP have little in common and have altogether different agendas.<br /> <br /> In large measure, CW is concerned with solution of computational problems which are stated in a natural language. Simple example. Given: Probably John is tall. What is the probability that John is short? What is the probability that John is very short? What is the probability that John is not very tall? A less simple example. Given: Usually Robert leaves office at about 5 pm. Typically it takes Robert about an hour to get home from work. What is the probability that Robert is home at 6:l5 pm.? What should be noted is that CW is the only system of computation which has the capability to deal with problems of this kind. The problem-solving capability of CW rests on two key ideas. First, employment of so-called restriction-based semantics (RS) for translation of a natural language into a mathematical language in which the concept of a restriction plays a pivotal role; and second, employment of a calculus of restrictions - a calculus which is centered on the Extension Principle of fuzzy logic.<br /> <br /> What is thought-provoking is that neither traditional mathematics nor standard probability theory has the capability to deal with computational problems which are stated in a natural language. Not having this capability, it is traditional to dismiss such problems as ill-posed. In this perspective, perhaps the most remarkable contribution of CW is that it opens the door to empowering of mathematics with a fascinating capability - the capability to construct mathematical solutions of computational problems which are stated in a natural language. The basic importance of this capability derives from the fact that much of human knowledge, and especially world knowledge, is described in natural language.<br /> <br /> In conclusion, only recently did I begin to realize that the formalism of CW suggests a new and challenging direction in mathematics - mathematical solution of computational problems which are stated in a natural language. For mathematics, this is an unexplored territory.</p>


2021 ◽  
Author(s):  
Nathan Ji ◽  
Yu Sun

The digital age gives us access to a multitude of both information and mediums in which we can interpret information. A majority of the time, many people find interpreting such information difficult as the medium may not be as user friendly as possible. This project has examined the inquiry of how one can identify specific information in a given text based on a question. This inquiry is intended to streamline one's ability to determine the relevance of a given text relative to his objective. The project has an overall 80% success rate given 10 articles with three questions asked per article. This success rate indicates that this project is likely applicable to those who are asking for content level questions within an article.


2013 ◽  
Vol 13 (4-5) ◽  
pp. 487-501 ◽  
Author(s):  
ROLF SCHWITTER

AbstractIn this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle.


2021 ◽  
Vol 2 (1) ◽  
pp. 43-48
Author(s):  
Merlin Florrence

Natural Language Processing (NLP) is rapidly increasing in all domains of knowledge acquisition to facilitate different language user. It is required to develop knowledge based NLP systems to provide better results.  Knowledge based systems can be implemented using ontologies where ontology is a collection of terms and concepts arranged taxonomically.  The concepts that are visualized graphically are more understandable than in the text form.   In this research paper, new multilingual ontology visualization plug-in MLGrafViz is developed to visualize ontologies in different natural languages. This plug-in is developed for protégé ontology editor. This plug-in allows the user to translate and visualize the core ontology into 135 languages.


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