本文關(guān)鍵詞：科學(xué)術(shù)語本體構(gòu)建的社會(huì)化方法　出處：《中國科學(xué)技術(shù)大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 科學(xué)術(shù)語本體 社會(huì)化投票 LDA 主題層級(jí) 領(lǐng)域關(guān)鍵詞表

【摘要】：一般來說,本體至少包含兩個(gè)要素：領(lǐng)域概念和概念之間的關(guān)系�？茖W(xué)術(shù)語本體指的是,在一個(gè)科學(xué)領(lǐng)域里,由領(lǐng)域概念和概念之間的層級(jí)關(guān)系構(gòu)成的一種簡單形式的本體�？茖W(xué)術(shù)語本體在科研項(xiàng)目管理、研究評價(jià)(Research Assessment Exercise)等活動(dòng)中扮演著極其重要的角色,因?yàn)榭茖W(xué)術(shù)語本體能夠準(zhǔn)確地將一個(gè)科學(xué)領(lǐng)域里的資源做詳細(xì)的分類,從而提高信息檢索效率。例如,在中國國家自然科學(xué)基金委,近幾年,平均每年都收到超過170,000份的基金申請書。平均來說,每個(gè)基金委的項(xiàng)目主任(Program Director)在不到三周的時(shí)間內(nèi),要負(fù)責(zé)超過1,500份申請書的項(xiàng)目評議專家指派工作。實(shí)踐當(dāng)中,大多數(shù)項(xiàng)目主任都采取這樣的策略：先把項(xiàng)目申請書分組,然后指派項(xiàng)目評議專家。為了幫助項(xiàng)目主任快速地、宏觀上把握所負(fù)責(zé)項(xiàng)目申請書的內(nèi)容,從而提高分組效率,我們亟需構(gòu)建科學(xué)術(shù)語本體。當(dāng)前術(shù)語本體構(gòu)建方法主要由兩類：一類是手工方式構(gòu)建,另外一類是自動(dòng)構(gòu)建。手工方式構(gòu)建術(shù)語本體一般由領(lǐng)域決策者(Domain Decision Makers)主導(dǎo),如基金委的管理人員、期刊編輯、本體工程師等。自動(dòng)構(gòu)建術(shù)語本體依賴于計(jì)算機(jī)算法處理自然語言。以質(zhì)量和效率兩方面作為標(biāo)準(zhǔn)來評價(jià)兩類術(shù)語本體構(gòu)建方法：手工方式構(gòu)建的術(shù)語本體一般質(zhì)量比較高,沒有噪音數(shù)據(jù),但是費(fèi)時(shí)費(fèi)力,并且對領(lǐng)域決策者的技能要求比較高。相比較而言,自動(dòng)方式構(gòu)建術(shù)語本體能夠在短時(shí)間內(nèi)處理大量數(shù)據(jù),并且能及時(shí)更新,但是這樣構(gòu)建的術(shù)語本體質(zhì)量較低,經(jīng)常有噪音數(shù)據(jù)。為了兼顧質(zhì)量和效率兩方面,我們提出了第三種術(shù)語本體構(gòu)建方法：社會(huì)化方式構(gòu)建術(shù)語本體。社會(huì)化方式構(gòu)建術(shù)語本體之所以可行,得益于我們所處的Web 2.0時(shí)代。各式各樣的社會(huì)化媒體能夠把人們方便地聚集在網(wǎng)絡(luò)上協(xié)同工作。尤其是科研社交網(wǎng)絡(luò)的興起(如ResearchGate、科研之友等)能夠使一個(gè)科學(xué)領(lǐng)域的學(xué)者跨越時(shí)間、空間交流。社會(huì)化方式構(gòu)建術(shù)語本體的本質(zhì)就是通過科研社交網(wǎng)絡(luò),鼓勵(lì)一個(gè)科學(xué)領(lǐng)域的學(xué)者積極參與到術(shù)語本體的構(gòu)建過程中去,從而減輕領(lǐng)域決策者的負(fù)擔(dān)。綜上所述,本文的研究問題是：如何以社會(huì)化的方式構(gòu)建科學(xué)術(shù)語本體?構(gòu)建一個(gè)科學(xué)領(lǐng)域的術(shù)語本體包含兩個(gè)核心的任務(wù)：(1)構(gòu)建領(lǐng)域關(guān)鍵詞表；(2)生成關(guān)鍵詞之間的層級(jí)關(guān)系。本文的研究目標(biāo)包含以下三個(gè)方面：(1)提出一個(gè)社會(huì)化方式構(gòu)建科學(xué)術(shù)語本體的統(tǒng)一可擴(kuò)展的理論框架；(2)設(shè)計(jì)社會(huì)化投票方式構(gòu)建領(lǐng)域關(guān)鍵詞表的方法并實(shí)現(xiàn)；(3)設(shè)計(jì)以關(guān)鍵詞相似度和專指度生成關(guān)鍵詞層級(jí)關(guān)系的方法。在信息系統(tǒng)研究領(lǐng)域,行為科學(xué)(Behavioral Science)和設(shè)計(jì)科學(xué)(Design Science)是兩個(gè)主要范式。行為科學(xué)致力于構(gòu)建和檢驗(yàn)理論(Theories),用以描述、解釋或預(yù)測人和組織的行為,設(shè)計(jì)科學(xué)專注于創(chuàng)造和檢驗(yàn)人工物(Artifacts),從而拓展人和組織的能力。本研究遵循設(shè)計(jì)科學(xué)研究方法。總體上,本文包含構(gòu)造(Build)和評價(jià)(Evaluate)兩個(gè)階段。在構(gòu)造階段,我們首先提出了以社會(huì)化投票方式構(gòu)建領(lǐng)域關(guān)鍵詞表的方法,其次設(shè)計(jì)了集成了LDA主題模型和包容層次結(jié)構(gòu)模型(Subsumption Hierarchy Model)的關(guān)鍵詞層級(jí)結(jié)構(gòu)生成方法。在評價(jià)階段,我們首先通過問卷(Survey)的方式評價(jià)了以社會(huì)化投票方式構(gòu)建領(lǐng)域關(guān)鍵詞表的方法,其次,以實(shí)驗(yàn)(Experiment)的方法對關(guān)鍵詞層級(jí)結(jié)構(gòu)生成方法的LDA主題模型部分進(jìn)行了評價(jià),再次,以實(shí)驗(yàn)的方法對關(guān)鍵詞層級(jí)結(jié)構(gòu)生成方法的包容層次結(jié)構(gòu)模型部分進(jìn)行了評價(jià),最后,以用戶研究(User Study)的方法對整個(gè)術(shù)語本體構(gòu)建方法進(jìn)行了評價(jià)。在理論上本研究(1)提出了一個(gè)社會(huì)化方式構(gòu)建科學(xué)術(shù)語本體的統(tǒng)一可擴(kuò)展的理論框架；(2)設(shè)計(jì)了以社會(huì)化投票方式構(gòu)建領(lǐng)域關(guān)鍵詞表的方法；(3)設(shè)計(jì)了以關(guān)鍵詞相似度和專指度生成關(guān)鍵詞層級(jí)關(guān)系的方法。在實(shí)踐方面,本研究提出的領(lǐng)域關(guān)鍵詞表構(gòu)建方法被應(yīng)用于中國國家自然科學(xué)基金委的項(xiàng)目評審工作中。據(jù)我們了解,全國科學(xué)技術(shù)名詞審定委員會(huì)每年都要耗費(fèi)大量的人力、物力做技術(shù)名詞規(guī)范工作,但大都用手工的方式,本研究為類似的組織提供了構(gòu)建科學(xué)領(lǐng)域術(shù)語本體的備擇方案。
[Abstract]:Generally speaking, the noumenon contains at least two elements: the relationship between the domain concept and the concept. The noumenon of scientific terms refers to a simple form of ontology formed by the hierarchy of concepts and concepts in a scientific field. The scientific term ontology evaluation on scientific project management, (Research Assessment Exercise) plays a very important role in the activities of scientific terminology because ontology can accurately be a science in the field of resources to do a detailed classification, so as to improve the efficiency of information retrieval. In China, for example, in recent years, the National Natural Science Foundation of China has received more than 170000 applications per year on average. On average, the Program Director of each fund committee is responsible for more than 1500 applications of project evaluation experts in less than three weeks. In practice, most project directors adopt such strategies: first group project applications, and then assign project experts. In order to help the project director to quickly and macroscopically grasp the content of the project application, so as to improve the efficiency of the group, we need to build the scientific terminology ontology. Currently, there are two main types of terminology ontology construction methods: one is constructed by hand, and the other is automatic. Manual construction of terminology ontology is generally dominated by Domain Decision Makers, such as fund managers, journal editors, ontology engineers, etc. Automatic construction of terminology ontology relies on computer algorithms for natural language processing. Two aspects of quality and efficiency are used as criteria to evaluate two kinds of terminology ontology construction methods: manually constructed noumenal ontology is generally of high quality and no noise data, but time-consuming and laborious, and has high skill requirements for domain decision makers. In contrast, automatic construction of term ontology can process large amounts of data in a short time and update in time, but the quality of noumenon constructed in this way is of low quality and often has noisy data. In order to take into account the two aspects of quality and efficiency, we have proposed third ways to construct the noumenon of terminology: the socialized way to construct the terminology ontology. The socialized way to build the terminology ontology is feasible, thanks to our Web 2 era. A variety of social media can easily gather people to work together on the network. In particular, the rise of scientific research social networks (such as ResearchGate, friends of scientific research, etc.) can enable scholars in a scientific field to cross over time and space. The essence of socialized way to build terminology ontology is to encourage a scientific scholar to participate in the construction of terminology ontology through scientific research social network, so as to lighten the burden of decision-makers in the field. To sum up, the research question in this paper is: how to build a scientific terminology ontology in a socialized way? To build a scientific term noumenon contains two core tasks: (1) building domain keywords list; (2) generating hierarchical relations between keywords. The goal of this paper includes the following three aspects: (1) proposed a unified theoretical framework to construct a scientific term ontology socialization mode can be extended; (2) the design of social voting method to build domain keyword list and implementation; (3) the design method of generating keywords hierarchy to keyword similarity and the specificity of the. In the field of information system research, Behavioral Science (Design) and Design Science (Design Science) are the main paradigms. Behavioral science is committed to building and testing theory (Theories), which is used to describe, explain or predict human and organizational behavior, design science to focus on creating and testing artifacts (Artifacts), so as to expand the capabilities of people and organizations. This study follows the design of scientific research methods. On the whole, this article contains two stages of structure (Build) and evaluation (Evaluate). In the construction stage, we first put forward a method of constructing domain keyword list based on social voting. Secondly, we designed a keyword hierarchy structure generation method which integrated LDA theme model and Subsumption Hierarchy Model. In the evaluation stage, we firstly through the questionnaire (Survey) of the evaluation methods of constructing, keyword tables to social voting, secondly, to experiment (Experiment) part of the LDA theme model of hierarchical structure keywords generation method of the method was evaluated again, experimental methods to the subsumption hierarchy model of keywords hierarchy the generation methods were evaluated, finally, to the user (User Study) of the method was evaluated for the term ontology construction method. In theory, this study (1) proposed a unified theoretical framework to construct a scientific term ontology socialization mode can be extended; (2) the design of the construction method of keyword table in social voting; (3) design method to generate keywords similarity and the specificity of the key words of the hierarchy. In practice, the construction method of domain keyword table proposed by this research is applied to the project evaluation work of the National Natural Science Foundation of China. According to our understanding, the national science and technology term Approval Committee consumes a lot of manpower and material resources to do technical nouns standardization work. But most of them use manual way, this study provides alternative programs for similar organizations to build ontology in scientific domain.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.1
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本文編號(hào)：1343262