Matches in SemOpenAlex for { <https://semopenalex.org/work/W2359288328> ?p ?o ?g. }
Showing items 1 to 67 of
67
with 100 items per page.
- W2359288328 abstract "ing; automatic knowledge acquisition; machine learning; natural language processing Abstract One of the most important signs of the information society is the explosion of information. information in Internet is out of order and is mostly written in natural languages which need to be processed by the technology of natural language processing. When you search for some certain information on Internet through a search engine, you might be confused by the huge amount of results which the search engine provides. However, if a search engine is embedded with Automatic Abstracting (AA) processing systems, you could locate the information quickly or you could get more information within a limited time. So, the AA technology is valuable both in science and application. work of this thesis was begun when we took over a project that is called The Key Technology Research of Computer Networks Providing Intelligent Information Services which belongs to the national 863 plan. One of the tasks is The Key Technology Research of Automatic Abstracting Systems of Chinese Text. As a member of this research group, I took part in designing and implementing an AA system called Literature Abstract and Digest Information Extract System(LADIES). From then on, I have been working in this field and this paper is the conclusion of my work. main topic of the thesis is AA technology. There are two parts of it. One is about the research of understanding based AA systems, and the other is about the invcestigation of Automatic Knowledge Acquistion(AKA) in AA systems. In the first part, the contents of AA technology are introduced and an understanding based AA model is put forward. Based on this model, LADIES is implemented. There are two major features of LADIES: (1) it understands text with the grammar, semantic and pragmatic information of words; (2) it chunks words into a relatively independent entity with chunking rules which are substitutes of syntactic analyzing rules. results demonstrate that it performs better than those statistical based AA systems. However, the application of LADIES is limited for its knowledge bases. And it is difficult to use in other fields because the knowledge bases are setup manually. So we investigate the techniques of automatic knowledge acquisition in order to solve the above problems to some extent. In the second part, we introduce the basic ideas of AKA and some Machine Learning (ML) methods which AKA applies. Then we propose a comprehensive dictionary model that contains grammar, semantic and pragmatic information of words. And we investigate a strategy of automatic learning pragmatic information for words. Also we put forward another strategy of automatic learning rule of salience sentences in texts and based on it, we establish an AA system LADIES NEW. Eventually, we suggest a AKA based AA system model called hierarchical feature extracting AA system model." @default.
- W2359288328 created "2016-06-24" @default.
- W2359288328 creator A5050423901 @default.
- W2359288328 date "2001-01-01" @default.
- W2359288328 modified "2023-09-23" @default.
- W2359288328 title "A Study of the Techniques of Automatic Abstracting and Knowledge Acquisition Systems" @default.
- W2359288328 hasPublicationYear "2001" @default.
- W2359288328 type Work @default.
- W2359288328 sameAs 2359288328 @default.
- W2359288328 citedByCount "0" @default.
- W2359288328 crossrefType "journal-article" @default.
- W2359288328 hasAuthorship W2359288328A5050423901 @default.
- W2359288328 hasConcept C110875604 @default.
- W2359288328 hasConcept C121158502 @default.
- W2359288328 hasConcept C136764020 @default.
- W2359288328 hasConcept C154945302 @default.
- W2359288328 hasConcept C161191863 @default.
- W2359288328 hasConcept C195324797 @default.
- W2359288328 hasConcept C202444582 @default.
- W2359288328 hasConcept C23123220 @default.
- W2359288328 hasConcept C26517878 @default.
- W2359288328 hasConcept C2777220311 @default.
- W2359288328 hasConcept C2779439875 @default.
- W2359288328 hasConcept C33923547 @default.
- W2359288328 hasConcept C38652104 @default.
- W2359288328 hasConcept C41008148 @default.
- W2359288328 hasConcept C9652623 @default.
- W2359288328 hasConceptScore W2359288328C110875604 @default.
- W2359288328 hasConceptScore W2359288328C121158502 @default.
- W2359288328 hasConceptScore W2359288328C136764020 @default.
- W2359288328 hasConceptScore W2359288328C154945302 @default.
- W2359288328 hasConceptScore W2359288328C161191863 @default.
- W2359288328 hasConceptScore W2359288328C195324797 @default.
- W2359288328 hasConceptScore W2359288328C202444582 @default.
- W2359288328 hasConceptScore W2359288328C23123220 @default.
- W2359288328 hasConceptScore W2359288328C26517878 @default.
- W2359288328 hasConceptScore W2359288328C2777220311 @default.
- W2359288328 hasConceptScore W2359288328C2779439875 @default.
- W2359288328 hasConceptScore W2359288328C33923547 @default.
- W2359288328 hasConceptScore W2359288328C38652104 @default.
- W2359288328 hasConceptScore W2359288328C41008148 @default.
- W2359288328 hasConceptScore W2359288328C9652623 @default.
- W2359288328 hasOpenAccess W2359288328 @default.
- W2359288328 hasRelatedWork W1008399548 @default.
- W2359288328 hasRelatedWork W1528307050 @default.
- W2359288328 hasRelatedWork W1568580077 @default.
- W2359288328 hasRelatedWork W1585692976 @default.
- W2359288328 hasRelatedWork W1608059655 @default.
- W2359288328 hasRelatedWork W1738006965 @default.
- W2359288328 hasRelatedWork W187411920 @default.
- W2359288328 hasRelatedWork W2011817723 @default.
- W2359288328 hasRelatedWork W2020015729 @default.
- W2359288328 hasRelatedWork W2035050715 @default.
- W2359288328 hasRelatedWork W2086979585 @default.
- W2359288328 hasRelatedWork W2104433957 @default.
- W2359288328 hasRelatedWork W2120872477 @default.
- W2359288328 hasRelatedWork W2149301260 @default.
- W2359288328 hasRelatedWork W2253068693 @default.
- W2359288328 hasRelatedWork W2255729922 @default.
- W2359288328 hasRelatedWork W2329628912 @default.
- W2359288328 hasRelatedWork W2988361819 @default.
- W2359288328 hasRelatedWork W2993235288 @default.
- W2359288328 hasRelatedWork W2169004162 @default.
- W2359288328 isParatext "false" @default.
- W2359288328 isRetracted "false" @default.
- W2359288328 magId "2359288328" @default.
- W2359288328 workType "article" @default.