The main property of the hierarchy is the ability to inherit subtypes qualities gipertipov: all characteristics that are inherent in animals, and mammalian, fish and birds. The basis of the theory of succession is the theory of syllogisms of Aristotle: If A - characteristic of B and B - x-ka C, then A Har-ka of all S.
The advantages of hierarchy and inheritance:
The type hierarchy is an excellent structure for indexing the knowledge base and its efficient organization.
Adherence to a branch with the help of the hierarchy is much faster.
SYNTACTIC ANALYSIS OF LANGUAGE AND ITS generation.
Semantic networks can help the grammer parsing to resolve the semantic ambiguity. Without this kind of representation the whole burden falls on the analysis of language syntax rules and semantic tests. The structure of the semantic network shows clearly how individual concepts are interconnected. When the grammer parsing encounters any ambiguity, it can use the semantic network in order to choose one or the other option. When you work with semantic networks used different techniques grammer parsing.
Parsing, which is based on the syntax. Work is controlled by the grammar grammer parser immediate constituents and operators of building structures and testing them. At that time, as the input data are analyzed, operators for constructing structures create a semantic network, and operators are testing check constraints on a partially constructed network. If no restrictions are not found, then used with the grammatical rule is rejected and the grammer parsing checks for another opportunity. This is the most common approach.
Parser using semantics. The grammer parsing operates using semantics as well as a parser, which is based on the syntax. However, it operates not with the syntactic categories such as the subject group and a group of predicate, and with the high-level concepts such as SHIP and transport.
Conceptual grammer parsing. Semantic network predicts the possible constraints that may arise in the relationship between words, as well as to predict the words that can meet later in the sentence. For example, the verb to give requires an animate agent, but also predicts the possibility of a recipient and an object, which will be given. Schenck was one of the most active supporters of the concept grammer parsing.
Parsing based on the examination of words. Due to the existence of a large number of irregular structures in natural language, many people, instead of going to any universal generalizations, use special dictionaries, a collection of several independent procedures, which are called by the experts of words. Analysis of the proposals considered as a process, carried out jointly by the various word-expert. The main proponent of this approach was Small.
Arguments for and against various grammer parsing techniques are often not based on specific data, and more on an already established opinion. And only one project in practice to compare several types of parsing - the language of semantic representations, a project developed at the University of Berlin. For several years they have created four different types of grammer parsers for the analysis of the German language and its writing into the language of semantic representations, which represents a network.
The first grammer parser was created in the likeness of a conceptual parser Shenk. It was noted that although adding to his vocabulary of new words was pretty easy, but the analysis could be conducted only in simple sentences, and only in relative clauses. Extend the syntactic processing of the parser was difficult.
Second semantically oriented grammer parser was extended network transition. It was easier to compile the syntax, but the apparatus syntax is slower than the first review of the parser.
Then the work was carried out with the word expert grammer parsing. Here you can easily were processed in special cases, but the dispersion between the individual components of the grammar makes it almost impossible its common understanding, support and modification.
Parser, which was created relatively recently - it is syntactically oriented parser, based on common grammar phrasal structure. He most The systematic and generalized and relatively quickly.
These results are basically consistent with the view of other linguists: a syntax-oriented grammer parsers most holistic, but they need a certain set of network operators for a smooth interaction between the grammar and semantic networks.
Generation of the language on a semantic network represents the inverse parsing. Instead of grammer parsing a chain with a view to generating network generator produces grammer parse language network for some chains. There are two ways of generating the language of the semantic network.
1. Generator of the language just to be on the network, turning concepts into words, and relations listed next to the arcs in the relationship of natural language. This method has many limitations.
2. Approaches targeted to control the generation of syntax language with the help of grammatical rules, which use the network in order to determine what the following rule should apply.
However, in practice, both methods have many similarities: for example, the first method is a sequence of nodes that are processed by the generator of language-oriented syntax.
Machine learning.
Graphs and networks are simple concepts for programs that are exploring new structures. Their advantage in learning is the ease of adding and removing, as well as the comparison of arcs and nodes. Below are the programs that are used to study semantic networks.
Winston used relational graphs to describe structures such as arches and towers. The machines are offered examples of correct and incorrect descriptions of these structures, and programs to create graphs, which pointed out all the necessary conditions to ensure that this structure is an arch or tower.
Salveter used graphs with the center of the verb for the submission of case relations, which require different verbs. His program MORAN for each verb displays declensional frame, comparing the same situation before and after their description using this verb.
Schenk developed a theory Memory-Organization Packets for an explanation of how people learn new information from the specific life situations. This MOP-it is a generalized abstract structure, which are not related to any particular situation individually.
Apply in practice.
Semantic networks can be written on almost any programming language on any machine. Most popular in this respect, languages LISP and PROLOG. However, many versions have been created and FORTRAN, PASCALe, C and other programming languages. To store all the nodes and arcs need more memory, although the first system were performed in 60-ies on the machines, which were much smaller and slower than today's computers.
One of the most common languages, designed for recording natural language in the form of networks - is PLNLP (Programming Language for Natural Language Processing) programming language for natural language processing, created Haydernom. This language is used for large grammars with extensive coverage. PLNLP works with two kinds of rules:
1. using the rules of decoding is grammer parsing the language of the linear chain and construct the network.
2. using the encoding rules network is generated by the scan chain, or other language transformed network.
In addition to special language for semantic networks was also developed special hardware. On conventional computers can be successfully carried out operations with language parsing and scanning operation of networks. However, for large knowledge bases to find the necessary rules or access to predznaniyam may take a very long time. To allow different processes take place simultaneously search Falman developed a system NETL, which is a semantic network, which can be used with parallel hardware. So he wanted to create a model of the human brain, which signals can move through different channels simultaneously. Other scientists have developed a parallel software for searching the most likely interpretation of ambiguous sentences of natural language.
Read also:
Knowledge based jobs
Graphs of quadratic equations
Academic proposal format
Semantic thesis
