CN110837564A - Construction method of knowledge graph of multilingual criminal judgment books - Google Patents
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Abstract
The invention provides a construction method of a knowledge graph of a multilingual criminal decision book, and relates to the field of computational linguistics. The criminal judgment book knowledge map with the Chinese and national languages fused is constructed, so that a more objective and reasonable expression mode can be obtained for making and proofreading the existing criminal judgment books, and the teaching and training mode and content of judicial practitioners can be improved and perfected. Meanwhile, the method can provide a standardized writing mode more carefully, realize cross-language comparison and query of professional knowledge, and can be widely applied to the fields of Chinese and national language referee documents and advanced intelligence.
Description
Technical Field
The invention relates to the technical field of computational linguistics, in particular to a construction method of a knowledge map of a multilingual criminal decision book.
Background
With the rapid development of computer technology and the continuous advance of intelligent judicial construction, the traditional manual examination and examination cannot meet the higher and higher requirements of people. It is desirable for the skilled practitioner to be able to bring more convenient work services and efficiency improvements to the machine. The network disclosure of official documents has made official documents of increasing interest to legal researchers and the public as a research or general material.
Research shows that the bilingual judges in the national region are in shortage and have gap in average business literacy. The criminal judgment books of national languages are required to be issued by the court to meet the requirements of national language users and are disclosed to the public in national regions when the criminal judgment books of national languages are related to the national regions, however, the production standardization of the criminal judgment books of the national language versions is not verified, the written contents are not corrected, and the expression of the criminal judgment books of the national language versions is not standardized. Thus, the method is not beneficial to maintaining the judicial image and is inconvenient for the masses to know the related information.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a construction method of a multilingual criminal judgment knowledge map, which is used for manufacturing a criminal judgment of a national language version through a multilingual criminal judgment text knowledge map, so that the technical problem that the expression of the criminal judgment of the national language version is irregular is solved.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention provides a construction method of a knowledge graph of a multilingual criminal decision book, which is executed by a computer and comprises the following steps of:
s1, acquiring a Chinese criminal judgment corpus, and preprocessing the Chinese criminal judgment corpus;
constructing a criminal decision term and law body knowledge base which consists of a legal term knowledge base, a criminal decision term knowledge base and a law article knowledge base;
s2, extracting criminal judgment attribute labels based on the preprocessed Chinese criminal judgment corpus, criminal judgment terms and a law body knowledge base;
s3, processing the criminal judgment book attribute label to form a criminal judgment book attribute label system and an extraction rule template;
s4, optimizing the criminal judgment term and law body knowledge base based on the criminal judgment attribute label system and the extraction rule template;
s5, acquiring an automatic criminal judgment statement labeling model based on the optimized criminal judgment statement terms and the law body knowledge base;
s6, automatically labeling the criminal judgment books based on a computer mode matching algorithm and the criminal judgment book automatic labeling model;
s7, extracting information of the automatically labeled criminal judgment books, and constructing a Chinese criminal judgment book knowledge map;
s8, constructing a national criminal decision knowledge map corresponding to the Chinese criminal decision knowledge map based on the mapping relation between Chinese and national languages; and combining the Chinese criminal judgment knowledge map to form the criminal judgment knowledge map integrating Chinese and national languages.
Preferably, in step S1, the specific process of preprocessing the corpus of chinese criminal decisions is as follows:
marking the first-level case in the Chinese criminal judgment book corpus; and dividing the internal structure of the criminal judgment book text in the Chinese criminal judgment book corpus.
Preferably, the step S3 specifically includes:
marking the attribute labels of the criminal judgment books, extracting rules, then checking, judging whether the marked text content is matched with the marking rules, if so, forming a criminal judgment book attribute label system and an extraction rule template, and if not, returning and marking again.
Preferably, in step S4, the method further includes: marking criminal judgment book terms and a law body knowledge base, extracting rules, then performing proofreading, judging whether the marked text content is matched with the marking rules, if so, forming a criminal judgment book attribute label system and an extraction rule template, and if not, returning and re-marking.
Preferably, the step S6 specifically includes:
s601, converting a criminal decision book from an unstructured criminal decision book text into a structured criminal decision book text by utilizing a computer mode matching algorithm and the automatic criminal decision book labeling model;
s602, extracting an attributive representation method of the criminal decision book text based on the structured criminal decision book text.
Preferably, in step S7, the information extraction specifically includes: analysis of discourse structure, sentence level extraction and word level extraction.
(III) advantageous effects
The invention provides a multilingual criminal decision book text knowledge map construction method. Compared with the prior art, the method has the following beneficial effects:
the method comprises the steps of extracting criminal decision book attribute labels from a preprocessed Chinese criminal decision book corpus, criminal decision book terms and a law body knowledge base, processing the criminal decision book attribute labels to form a criminal decision book attribute label system and an extraction rule template, optimizing and perfecting the criminal decision book terms and the law body knowledge base based on the criminal decision book attribute label system and the extraction rule template, then obtaining an automatic criminal decision book labeling model according to the criminal decision book terms and the law body knowledge base, automatically labeling the criminal decision books by combining the criminal decision book automatic labeling model with a computer mode matching algorithm, extracting information of the labeled criminal decision books, and constructing a Chinese criminal decision knowledge map; and finally, constructing a national criminal decision knowledge map corresponding to the Chinese criminal decision knowledge map through the mapping relation between Chinese and national languages, and combining the Chinese criminal decision knowledge map to form the Chinese and national language integrated criminal decision knowledge map. The criminal judgment book knowledge map with the Chinese and national languages fused is constructed, so that a more objective and reasonable expression mode can be obtained for making and proofreading the existing criminal judgment books, and the teaching and training mode and content of judicial practitioners can be improved and perfected. Meanwhile, the method can provide a standardized writing mode more carefully, realize cross-language comparison and query of professional knowledge, and can be widely applied to the fields of Chinese and national language referee documents and advanced intelligence.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of a method for constructing a knowledge-graph of multilingual criminal decisions according to an embodiment of the present invention;
FIG. 2 is a framework of an automatic labeling model of criminal adjudication;
fig. 3 is a schematic diagram of an information extraction process.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a construction method of the multilingual criminal judgment knowledge map, and the construction method of the multilingual criminal judgment knowledge map provides a regular writing template for national criminal judgment, so that the problem of non-standard expression of national criminal judgment is solved, and the objective and reasonable expression mode of the national criminal judgment is realized.
In order to solve the technical problems, the general idea of the embodiment of the application is as follows:
the embodiment of the invention extracts criminal judgment book attribute labels from a preprocessed Chinese criminal judgment book corpus, criminal judgment book terms and a law body knowledge base, then processes the criminal judgment book attribute labels to form a criminal judgment book attribute label system and an extraction rule template, optimizes and perfects the criminal judgment book terms and the law body knowledge base based on the criminal judgment book attribute label system and the extraction rule template, then obtains a criminal judgment book automatic labeling model according to the criminal judgment book terms and the law body knowledge base, automatically labels the criminal judgment books by combining the criminal judgment book automatic labeling model with a computer mode matching algorithm, extracts information of the labeled criminal judgment books, and constructs a Chinese criminal judgment book knowledge map; and finally, constructing a national criminal decision knowledge map corresponding to the Chinese criminal decision knowledge map through the mapping relation between Chinese and national languages, and combining the Chinese criminal decision knowledge map to form the Chinese and national language integrated criminal decision knowledge map. The criminal judgment book knowledge map with the Chinese and national languages fused constructed by the embodiment of the invention can enable the existing criminal judgment book to be manufactured and proofread in a more objective and reasonable expression mode, and is helpful for improving and perfecting the education and training modes and contents of judicial staff.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
The embodiment of the invention provides a construction method of a knowledge graph of multilingual criminal judgment books, which comprises the following steps of:
s1, acquiring a Chinese criminal judgment corpus, and preprocessing the Chinese criminal judgment corpus;
constructing a criminal decision term and law body knowledge base which consists of a legal term knowledge base, a criminal decision term knowledge base and a law article knowledge base;
s2, extracting criminal judgment attribute labels based on the preprocessed Chinese criminal judgment corpus, criminal judgment terms and a law body knowledge base;
s3, processing the criminal judgment book attribute label to form a criminal judgment book attribute label system and an extraction rule template;
s4, optimizing the criminal judgment term and law body knowledge base based on the criminal judgment attribute label system and the extraction rule template;
s5, acquiring an automatic criminal judgment statement labeling model based on the optimized criminal judgment statement terms and the law body knowledge base;
s6, automatically labeling the criminal judgment books based on a computer mode matching algorithm and the criminal judgment book automatic labeling model;
s7, extracting information of the automatically labeled criminal judgment books, and constructing a Chinese criminal judgment book knowledge map;
s8, constructing a national criminal decision knowledge map corresponding to the Chinese criminal decision knowledge map based on the mapping relation between Chinese and national languages; and combining the Chinese criminal judgment knowledge map to form the criminal judgment knowledge map integrating Chinese and national languages.
The criminal judgment book knowledge map with the Chinese and national languages fused constructed by the embodiment of the invention can enable the existing criminal judgment book to be manufactured and proofread in a more objective and reasonable expression mode, and is helpful for improving and perfecting the education and training modes and contents of judicial staff.
The following describes each step in detail, as shown in FIGS. 1 to 3.
Here, national languages are exemplified by mongolian languages.
And S1, acquiring a Chinese criminal judgment corpus and preprocessing the Chinese criminal judgment corpus. And constructing a criminal decision term and law body knowledge base which consists of a legal term knowledge base, a criminal decision term knowledge base and a law article knowledge base. The method specifically comprises the following steps:
s101, obtaining criminal judgment book corpus in a network crawling or manual downloading mode, and constructing a Chinese criminal judgment book corpus.
S102, marking 11 primary cases in the Chinese criminal judgment corpus, and dividing the internal structure of the criminal judgment text in the Chinese criminal judgment corpus.
Wherein, 11 kinds of first-class patterns refer to: the method is characterized by harming national security, public security, destroying the economic order of socialist market, infringing the civilian rights of citizens, infringing property, hindering the social management order, harming the national defense benefits, bribery, profane, soldier infringes responsibilities and criminal case terrestris nine-seven months ago.
The internal structure of criminal decision book text is divided into the following structures: the system comprises a head part, a tail part and texts, wherein the head part and the tail part comprise information such as a public complaint organ, an advertiser, gender, birth date, nationality, cultural degree, criminal reasons, and prosecution names, and the texts comprise information such as facts, reasons and judgment results.
S103, establishing a criminal decision term and law body knowledge base which consists of a legal term knowledge base, a criminal decision term knowledge base and a law and regulation knowledge base.
And S2, extracting criminal decision book attribute labels based on the preprocessed Chinese criminal decision book corpus, criminal decision book terms and a law body knowledge base. In a specific implementation process, the number of the attribute tags is 149, wherein the number of the first-level attribute tags is 6, the number of the second-level attribute tags is 24, the number of the third-level attribute tags is 112, and the number of the fourth-level attribute tags is 7.
S3, processing the criminal judgment book attribute label to form a criminal judgment book attribute label system and an extraction rule template. The method specifically comprises the following steps:
marking the attribute labels of the criminal judgment books, extracting rules, then checking, judging whether the marked text content is matched with the marking rules, if so, forming a criminal judgment book attribute label system and an extraction rule template, and if not, returning and marking again.
S4, optimizing and perfecting criminal judgment term and law body knowledge base based on the criminal judgment attribute label system and the extraction rule template. In the specific implementation process, criminal judgment book terms and law body knowledge base pairs are required to be labeled, rules are extracted, then proofreading is carried out, whether the labeled text content is matched with the labeling rules or not is judged, if yes, a criminal judgment book attribute label system and an extraction rule template are formed, and if not, returning and labeling are carried out again, and a loop process is formed with the step S3.
And S5, acquiring an automatic criminal decision statement labeling model based on the optimized and perfected criminal decision statement terms and the law body knowledge base. In the specific implementation process, the criminal decision book automatic labeling model comprises the following structures as shown in fig. 2: an input layer, a label layer and an output layer. Inputting a plurality of criminal judgment books and a law term knowledge base on an input layer, entering rules for criminal judgment books on a labeling layer for extraction, labeling attributes of the plurality of criminal judgment books through a criminal judgment book attribute label system after the rules are extracted, and outputting the labeled criminal judgment books and the plurality of labeled criminal judgment books on an output layer to form the labeled criminal judgment book knowledge base.
And S6, automatically labeling the criminal judgment books based on a computer mode matching algorithm and the criminal judgment book automatic labeling model. The method specifically comprises the following steps:
s601, converting a criminal decision book from an unstructured criminal decision book text into a structured criminal decision book text by utilizing a computer mode matching algorithm and the automatic criminal decision book labeling model;
s602, extracting an attributive representation method of the criminal decision book text based on the structured criminal decision book text.
And S7, extracting information of the automatically labeled criminal judgment books, and constructing a Chinese criminal judgment book knowledge map.
In the specific implementation process, as shown in fig. 3, information extraction is performed on a plurality of automatically labeled criminal judgment books, and the information extraction process includes analysis of discourse structure, sentence level extraction, and word level extraction. Firstly, in the analysis process of the chapter structure, a criminal decision book is divided from unstructured criminal decision book texts and structured criminal decision book texts by a computer pattern matching algorithm. Wherein the unstructured criminal decision book text comprises: text information, text-fact information, and text-reason information. The structured criminal adjudication text includes: header, trailer, and body-the decision result.
In the sentence-level extraction process, the text information of the criminal judgment book text is divided into sentences, and the fact information and the reason information in the text are matched through a computer pattern matching algorithm. Wherein the text-fact information includes control party instruction information, evidence information, court approval information, debtor opinions, culprit information, indemnity information, and crime preparation information. The text-reason information includes: criminal action information and forensic information.
In the word-level extraction process, information obtained by discourse structure analysis and sentence-level extraction is combined, rule extraction is carried out on the information, and then attribute labeling is carried out. And finally, converting the criminal judgment books subjected to discourse structure analysis, sentence level extraction and word level extraction into XML documents and storing the XML documents to construct a Chinese criminal judgment book knowledge map.
S8, constructing a national criminal judgment knowledge map corresponding to the Chinese criminal judgment knowledge map based on the mapping relation between the Chinese language and the national language to form the criminal judgment knowledge map integrating the Chinese language and the national language. In the specific implementation process, based on the mapping relation between Chinese and Mongolian, the Chinese criminal judgment knowledge map is converted into the Mongolian criminal judgment knowledge map, and the Chinese criminal judgment knowledge map and the Mongolian criminal judgment knowledge map are integrated to form the Chinese and Mongolian integrated criminal judgment knowledge map. According to the criminal judgment book knowledge map with Chinese and Mongolian languages fused, a standardized writing mode is provided for Mongolian languages.
In summary, compared with the prior art, the method has the following beneficial effects:
1. the criminal judgment book knowledge map with the Chinese and national languages fused constructed by the embodiment of the invention can enable the existing criminal judgment book to be manufactured and proofread in a more objective and reasonable expression mode, and is helpful for improving and perfecting the education and training modes and contents of judicial staff.
2. The embodiment of the invention realizes the automatic marking of the Chinese and national bilingual criminal judgment book text by using a computer mode matching method, improves the cross-language retrieval and bilingual judgment auxiliary level in the professional field, and can be widely applied to the fields of Chinese and national language judgment documents and advanced intelligence.
It should be noted that, through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A method of constructing a knowledge-graph of multilingual criminal decisions, the method being implemented by a computer and comprising the steps of:
s1, acquiring a Chinese criminal judgment corpus, and preprocessing the Chinese criminal judgment corpus;
constructing a criminal decision term and law body knowledge base which consists of a legal term knowledge base, a criminal decision term knowledge base and a law article knowledge base;
s2, extracting criminal judgment attribute labels based on the preprocessed Chinese criminal judgment corpus, criminal judgment terms and a law body knowledge base;
s3, processing the criminal judgment book attribute label to form a criminal judgment book attribute label system and an extraction rule template;
s4, optimizing the criminal judgment term and law body knowledge base based on the criminal judgment attribute label system and the extraction rule template;
s5, acquiring an automatic criminal judgment statement labeling model based on the optimized criminal judgment statement terms and the law body knowledge base;
s6, automatically labeling the criminal judgment books based on a computer mode matching algorithm and the criminal judgment book automatic labeling model;
s7, extracting information of the automatically labeled criminal judgment books, and constructing a Chinese criminal judgment book knowledge map;
s8, constructing a national criminal decision knowledge map corresponding to the Chinese criminal decision knowledge map based on the mapping relation between Chinese and national languages; and combining the Chinese criminal judgment knowledge map to form the criminal judgment knowledge map integrating Chinese and national languages.
2. The method for constructing a knowledge-graph of multilingual criminal decisions according to claim 1, wherein in step S1, the specific process of preprocessing the corpus of chinese criminal decisions is as follows:
marking the first-level case in the Chinese criminal judgment book corpus; and dividing the internal structure of the criminal judgment book text in the Chinese criminal judgment book corpus.
3. The method for constructing a knowledge-graph of multilingual criminal decisions of claim 1, wherein the step S3 is specifically comprised of:
marking the attribute labels of the criminal judgment books, extracting rules, then checking, judging whether the marked text content is matched with the marking rules, if so, forming a criminal judgment book attribute label system and an extraction rule template, and if not, returning and marking again.
4. The method for constructing a knowledge-graph of multilingual criminal decisions of claim 3, wherein in step S4, further comprising: marking criminal judgment book terms and a law body knowledge base, extracting rules, then performing proofreading, judging whether the marked text content is matched with the marking rules, if so, forming a criminal judgment book attribute label system and an extraction rule template, and if not, returning and re-marking.
5. The method for constructing a knowledge-graph of multilingual criminal decisions of claim 1, wherein the step S6 is specifically comprised of:
s601, converting a criminal decision book from an unstructured criminal decision book text into a structured criminal decision book text by utilizing a computer mode matching algorithm and the automatic criminal decision book labeling model;
s602, extracting an attributive representation method of the criminal decision book text based on the structured criminal decision book text.
6. The method for constructing a knowledge-graph of multilingual criminal decisions of claim 5, wherein in step S7, the information extraction comprises: analysis of discourse structure, sentence level extraction and word level extraction.
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|---|---|---|---|---|
| CN111737412A (en) * | 2020-05-21 | 2020-10-02 | 电子科技大学 | Citizen visiting guiding method based on natural language processing and knowledge graph |
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| CN112199511A (en) * | 2020-09-28 | 2021-01-08 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Cross-language multi-source vertical domain knowledge graph construction method |
| CN112445915A (en) * | 2021-01-28 | 2021-03-05 | 京华信息科技股份有限公司 | Document map extraction method and device based on machine learning and storage medium |
| CN113239130A (en) * | 2021-06-18 | 2021-08-10 | 广东博维创远科技有限公司 | Criminal judicial literature-based knowledge graph construction method and device, electronic equipment and storage medium |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101576909A (en) * | 2009-05-11 | 2009-11-11 | 内蒙古蒙科立软件有限责任公司 | Mongolian digital knowledge base system construction method |
| CN104133848A (en) * | 2014-07-01 | 2014-11-05 | 中央民族大学 | Tibetan language entity knowledge information extraction method |
| CN104809176A (en) * | 2015-04-13 | 2015-07-29 | 中央民族大学 | Entity relationship extracting method of Zang language |
| CN107122444A (en) * | 2017-04-24 | 2017-09-01 | 北京科技大学 | A kind of legal knowledge collection of illustrative plates method for auto constructing |
| CN107273106A (en) * | 2016-04-08 | 2017-10-20 | 北京三星通信技术研究有限公司 | Object information is translated and derivation information acquisition methods and device |
| CN107589826A (en) * | 2016-07-07 | 2018-01-16 | 深圳狗尾草智能科技有限公司 | The man-machine interaction method and system of knowledge based collection of illustrative plates |
| CN108009299A (en) * | 2017-12-28 | 2018-05-08 | 北京市律典通科技有限公司 | Law tries method and device for business processing |
| CN108197163A (en) * | 2017-12-14 | 2018-06-22 | 上海银江智慧智能化技术有限公司 | A kind of structuring processing method based on judgement document |
| CN108334500A (en) * | 2018-03-05 | 2018-07-27 | 上海思贤信息技术股份有限公司 | A kind of judgement document's mask method and device based on machine learning algorithm |
| CN108681977A (en) * | 2018-03-27 | 2018-10-19 | 成都律云科技有限公司 | A kind of lawyer's information processing method and system |
| CN109271529A (en) * | 2018-10-10 | 2019-01-25 | 内蒙古大学 | Cyrillic Mongolian and the double language knowledge mapping construction methods of traditional Mongolian |
-
2019
- 2019-09-25 CN CN201910909778.7A patent/CN110837564B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101576909A (en) * | 2009-05-11 | 2009-11-11 | 内蒙古蒙科立软件有限责任公司 | Mongolian digital knowledge base system construction method |
| CN104133848A (en) * | 2014-07-01 | 2014-11-05 | 中央民族大学 | Tibetan language entity knowledge information extraction method |
| CN104809176A (en) * | 2015-04-13 | 2015-07-29 | 中央民族大学 | Entity relationship extracting method of Zang language |
| CN107273106A (en) * | 2016-04-08 | 2017-10-20 | 北京三星通信技术研究有限公司 | Object information is translated and derivation information acquisition methods and device |
| CN107589826A (en) * | 2016-07-07 | 2018-01-16 | 深圳狗尾草智能科技有限公司 | The man-machine interaction method and system of knowledge based collection of illustrative plates |
| CN107122444A (en) * | 2017-04-24 | 2017-09-01 | 北京科技大学 | A kind of legal knowledge collection of illustrative plates method for auto constructing |
| CN108197163A (en) * | 2017-12-14 | 2018-06-22 | 上海银江智慧智能化技术有限公司 | A kind of structuring processing method based on judgement document |
| CN108009299A (en) * | 2017-12-28 | 2018-05-08 | 北京市律典通科技有限公司 | Law tries method and device for business processing |
| CN108334500A (en) * | 2018-03-05 | 2018-07-27 | 上海思贤信息技术股份有限公司 | A kind of judgement document's mask method and device based on machine learning algorithm |
| CN108681977A (en) * | 2018-03-27 | 2018-10-19 | 成都律云科技有限公司 | A kind of lawyer's information processing method and system |
| CN109271529A (en) * | 2018-10-10 | 2019-01-25 | 内蒙古大学 | Cyrillic Mongolian and the double language knowledge mapping construction methods of traditional Mongolian |
Non-Patent Citations (4)
| Title |
|---|
| 耿雪来: "面向旅游的蒙汉双语知识图谱的研究与构建", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 * |
| 耿雪来: "面向旅游的蒙汉双语知识图谱的研究与构建", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》, no. 09, 15 September 2019 (2019-09-15), pages 138 - 1308 * |
| 赵小兵 等: "多民族语言本体知识库构建技术", 《中文信息报》 * |
| 赵小兵 等: "多民族语言本体知识库构建技术", 《中文信息报》, vol. 25, no. 04, 31 July 2011 (2011-07-31), pages 71 - 74 * |
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|---|---|---|---|---|
| CN111737412A (en) * | 2020-05-21 | 2020-10-02 | 电子科技大学 | Citizen visiting guiding method based on natural language processing and knowledge graph |
| CN112001159A (en) * | 2020-08-24 | 2020-11-27 | 平安国际智慧城市科技股份有限公司 | Document generation method and device, electronic equipment and storage medium |
| CN112199511A (en) * | 2020-09-28 | 2021-01-08 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Cross-language multi-source vertical domain knowledge graph construction method |
| CN112199511B (en) * | 2020-09-28 | 2022-07-08 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | Cross-language multi-source vertical domain knowledge graph construction method |
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| CN113239130A (en) * | 2021-06-18 | 2021-08-10 | 广东博维创远科技有限公司 | Criminal judicial literature-based knowledge graph construction method and device, electronic equipment and storage medium |
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