Summary of description logic

Transactions on Computer Science and Technology September 2014, Volume 3, Issue 3, PP.98-101

Summary of Description Logic Chun Gui, Yabin Shao Mathematics and Computer Science College, Northwest University for Nationalities, Lanzhou 730030, China #

Email: guichun2103@aliyun.com

Abstract Description logic is a formal language of knowledge representation and is the first-order logic which can determine subset.

Description logic, as an effective mechanism for knowledge representation, is widely applied to many areas of computer science.

This paper is about the application research and present situation of description logic, it provides a system expounds about description logic in definition, basic syntax and semantics, the structure of the system, the status in semantic Web and so on.

Keywords: Description Logic; Tbox; Abox; Knowledge Representation

1 INTRODUCTION Description logic (named DLs for short) is a formalized language of knowledge representation[1], suitable for knowledge in concept and the concept hierarchy. DLs unified logic base on such as Frames, Semantic Networks, Semantic Data Models and so on, presented to us a formalized, based on the logical semantics. The basic building blocks of DLs are concept, role and individual. The feature of DLs is from a lot of structural descriptors to simple concepts, to build more complex concepts. The center of DLs is reasoning, which can explicitly contain knowledge derived from the knowledge base of implied knowledge, DLs main reasoning classification, satisfiability problem detection, containment relationship and instance test.

The Knowledge Base of DLs usually contains two parts: Tbox and Abox. Among them, Tbox is a set of collection contains the assertion about concepts and relationship, we can deduce general attributes of concepts and relationships from the Tbox; Abox is a set of instances of assertion about individuals, instance assert that an individual is a concept and a relationship between two individuals.

Four basic components of DLs: the tectonic operator set which is used for concept and structure of relational expression; the axiom types allowed in Tbox; the assertion type allowed in Abox; the reasoning mechanism in Tbox and Abox reasoning.

2 OVERVIEW OF DESCRIPTION LOGIC This section arranged to introduce the development of DLs, introduces the main method of knowledge representation, the syntax and semantics of the DLs.

2.1 The Development of DLs Expressed in literature[2] is the description language expression ability and the contradiction between the complexity of reasoning, this major contribution was completed by Ron Brachman and Hector Levesque. The paradox is that the representation of a description language ability can not too strong, because it may cause the undecidable reasoning; description language, on the other hand, the representation of a language can't be too weak, or not enough to say knowledge in the field of application .This contradiction become an important subject of DLs study, based on the research progress of the problem, the development of DLs can be divided into the following four stages[3]: The first stage: the main concern for the implementation of some system, such as KLONE[4], K - REP[5], the BACK[6] and LOOM[7]. The disadvantage of these algorithms is that they are completed only for weak expressing ability DLs, for strong expressing ability DLs, can't detect the existing instances of inclusion or relationship.

The second stage: development and implement the algorithm of the system based on table, such as Kris, Crack, - 98 http://www.ivypub.org/cst

began reasoning complexity analysis of the various DLs. The third stage: for all kinds of ability of DLs, many optimized tableau algorithm had been developed. There is a detailed study for the relationship between DLs and modal logic, DLs and determined subset of first-order logic.

The fourth stage: developed the commercial value DL system. DLs has high priority in the field of computer science and have been promoted and applied.

2.2 The Main Method of Knowledge Representation The knowledge representation is developed in the 1970s, and divided into two categories.

The first category: knowledge representation method based on logic: representation language usually takes the variation of first order predicate logic, reasoning is equivalent to prove logic inference. Expression ability of firstorder logic must be restrained, otherwise it may damage the knowledge structure, lead to ineffective reasoning results.

The second category: knowledge representation method not based on logic: usually is based on the use of graphical interface, knowledge in some special data structure to represent, reasoning can be simply completed by processing structure which is a special process.

Semantic networks and frames are very important in knowledge representation methods of the two methods.

However. But due to semantic networks and frames are the lack of precise semantics, it is not satisfactory in real system performance, so the frames based on first-order logic, given the semantics, which makes the knowledge representation had taken an important step forward again.

2.3 DLs Syntax and Semantics IN DLs, the most basic description language in the description languages is ALC. Other languages are the extension of ALC, make a distinction among description languages according to the structure character. Usually use A and B express atoms concept, R express atom relationship, C and D express concept description, I is an explanation, ALC syntax and semantics can be used in Table 1.

TABLE 1 ALC SYNTAX AND SEMANTICS tectonic operator atomic concept top concept bottom concept atomic negation concept negation concept disjunction concept conjunction

syntax A T

semantics I I A  I

 \ AI I \ CI I I C ∪D



﹁A ﹁C C∪D C

instance Human Male  Male Man  Man Man

I

∩D

C

I

∩D

Man Woman Human  Male

I

existential quantification

R.C

{a  I | b.(a, b)  R I  b  C I }

has  Child .Male

value restriction

R.C

{a  | b.(a, b)  R  b  C }

has  Child .Doctor

I

I

I

3 APPLICATION OF DLS Now, the DLs has been used in software engineering, configuration, and query mechanism, the layout system and natural language processing, etc. DL as an ontology language, in the semantic web, has played a huge role.

3.1 Application in Semantic Web Now, the information on the Web is growing in new Moore's law, but a lot of information lack of unified description of the form, brings difficulties to network resource management. In addition, most of the miss system on Web are the way of such as HTML, makes the computer can't identify the content of the page. Information browsing, extraction, processing and so on, all need artificial participation, more serious is that large amount of information is probably irrelevant, it greatly reduces the information query precision and recall rate. In order to achieve the intelligent Web, - 99 http://www.ivypub.org/cst

Tim Berners-lee put forward a new generation of network - the semantic Web, in 2001.Semantic web for information on the world wide web have well-defined meaning, can help humans and computers communicate with each other better and work together.

At present, the semantic web concepts is heating up, DLs will play a huge role.

3.2 Application in Natural Language Processing In the early, KL - ONE system is used in natural language processing in semantic interpretation, this is one of the main application of DLs, literature [8] makes a detail introduction about driven semantic interpretation and the generation of natural language process.

3.3 Application in Information Systems Based on Web There are two main important ontology language OIL and DAML + OIL, which is the DLs’application of information system based on web.

In addition to above introduction, DLs in configuration, in the digital library, in database also has a very wide application.

4 THE RESEARCH STATUS OF DLS DLs often deal with the concept of meaning, but in real life, many of the concepts without a precise definition, for example, the concept of "big". As a result, people can only in a way to judge concept instance. Therefore, literature [9] proposed a concept of fuzzy description logic, the concept of using fuzzy predicate to deal with ambiguity and inaccuracy, combine DLs and fuzzy logic, a general framework is put forward, on the basis of DL ALC defines the syntax and semantics of the fuzz DL, deductive reasoning and constraint computation, it provides an application foundation for the new generation of description to process fuzzy concept. Common are temporal description logic and dynamic description logics.

5 CONCLUSION DLs from appearing to now has been able to get so much attention mainly because (1) the DLs has clearly model theoretical mechanism; 2) suitable for represented by concept taxonomy application field; 3) provides a useful service of reasoning. DLs has great potential for application and research, more research work is needed.

ACKNOWLEDGMENT This work is supported by the Fundamental Research Funds for the Central Universities 2014: 31920140089 and the National Natural Science Foundation of China: 11161041.

REFERENCES [1]

Description Logic. home page http://dl.kr.org

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Franconi E. Natural Language Processing In:Baader E, McGuinness D, Nardi D, et al. eds. The Description Logic Handbook: Theory. Implementation and Applications, chapter 15, Cambridge University Press, 2003 - 100 http://www.ivypub.org/cst

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Straccia U. A Fuzzy Description Logic. In: Proceedings of AAAI-98. 15th Conference of the American Association for Artificial Intelligence

AUTHORS 1

Chun Gui, borned in 1981, Educational background: Lanzhou university master degree of computer application

technology, Lanzhou, China

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