Hierarchical semantic tree construction method and system for language understanding

A construction method and language understanding technology, applied in the field of hierarchical semantic tree construction methods and systems, can solve the problems of not necessarily ideal effect, strong domain dependence, effect discount, etc., to achieve the effect of improving readability and accuracy

Inactive Publication Date: 2014-11-12
BEIJING NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

The schema of the entity is defined in this scheme, which includes semantic type and probability, Markov probability, and semantic rules. The acquisition of these semantic content requires training of large-scale data, ...

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  • Hierarchical semantic tree construction method and system for language understanding
  • Hierarchical semantic tree construction method and system for language understanding
  • Hierarchical semantic tree construction method and system for language understanding

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Embodiment 1

[0047] Provide a kind of hierarchical semantic tree construction method and system for language comprehension in the present embodiment, semantic tree is the semantic structure tree, is for a sentence in natural language, refers to the feature word block (core verb) in a sentence lexical chunk) and the semantic relationship between other chunks determined by it. For example, the characteristic chunk V in a sentence is a verb expressing action, which determines that there must be actor chunks, object chunks, and content chunks in this sentence. Only in this way can the semantics of the sentence be complete. Although one of the latter three can be omitted in a certain context, these four chunks are the necessary components for the complete semantics of a sentence, and they are also called main chunks. In contrast, auxiliary language chunks are not necessary components for the establishment of a sentence, but mainly express the way, means, way, condition, time, etc. of an action....

Embodiment 2

[0076] A specific method for constructing a hierarchical semantic tree is given in this embodiment, and the basic flow of the scheme is also as follows figure 1 As shown, the method 100 for constructing a hierarchical semantic tree in this embodiment begins at step S110 by inputting the sentence to be processed, and then preprocessing the sentence to be processed in step S120, that is, performing word segmentation on the sentence to be processed according to the domain dictionary and the general dictionary, and loading Semantic knowledge of words, semantic knowledge mainly includes six generalized concept classes of words, namely V (dynamic), G (static), W (object), P (person), U (attribute), L (logic) and Several subcategories under its overall planning; secondly, in step S130, identify the semantic nodes of the statement and distinguish its levels, the first step is to use the LV rule to identify all semantic nodes to the result after word segmentation, the second step It is...

Embodiment 3

[0110] A specific application example is given in this embodiment, Figure 4 and Figure 5 is a diagram illustrating the result of building a hierarchical semantic tree for an example sentence. like Figure 4As shown, the sentence to be processed is "the web browser uses the uniform resource locator to send the HTML request to the server controlled by the system.", and the semantic tree structure at the clause level is: GBK1 "web browser" + ABK "use uniform resource The locator "+L0" sends the "+GBK2" HTML request "+EG" to "+GBK3" the server controlled by the system", wherein the CHK_SST (period) block is used as the root node. The semantic nodes of the first level are L1 (use), L0 (will), V (send to), and all three levels are 0; the semantic edges of the first level are CHK_ABK (use uniform resource locator), CHK_L0 (will ), CHK_EG (sent to), CHK_GBK (web browser, HTML request, remote server), the six language block levels are all 0, and it hangs out as a child node of the...

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Abstract

The invention discloses a hierarchical semantic tree construction method and system for language understanding. The method mainly comprises the steps as follows: segmenting terms of a statement and loading a semantic knowledge base; recognizing all nodes of the statement according to an LV rule, and recognizing the level of the nodes according to semantic knowledge and term positions and collocations; generating a special node by punctuation at the end of the statement, and taking the special node as a root node of a semantic tree; merging the nodes according to generated node information, recognizing semantic side chunks of the statement, and taking a level-0 semantic side as a child node to be hung on the root node; circularly traversing all child nodes of the statement till no low-level semantic side exists, and taking the child nodes as leaf nodes to be hung on the child node. According to the hierarchical semantic tree construction method and system, under the condition that no syntactic resource exists, the semantic structure tree is obtained through semantic information and the term positions and collocations only, so that a computer can enter a deep semantic layer of a natural language, various processing of the natural language can be finished on the basis of understanding, the first step of semantic understanding of the natural language is realized, and the hierarchical semantic tree construction method and system can be applied to information retrieval, automatic abstraction, machine translation, text categorization, information filtration and the like.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a method and a system for constructing a hierarchical semantic tree obtained by using semantic knowledge and the position and collocation of words. Background technique [0002] With the development of electronic information technology, digital information resources are widely used more and more. This requires that machines can also understand natural language, and complete various processing of natural language on the basis of "understanding", such as information retrieval, automatic summarization, machine translation, text classification, and information filtering. It can be seen that enabling computers to enter the semantic depth of natural language is a condition for achieving the above purpose. In order for a machine to understand the meaning of natural language, it must first understand the structure of natural language sentences. Sentence structure is a basic st...

Claims

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Application Information

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IPC IPC(8): G06F17/27
Inventor 晋耀红朱筠刘小蝶
Owner BEIJING NORMAL UNIVERSITY
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