University of Macau / Faculty of Arts and Humanities / Department of Chinese

University of Macau / Faculty of Arts and Humanities / Department of Chinese

現今資料大量且快速數位化的時代，各領域對資訊探勘分析技術越趨倚重。而在數位人文中領域中從2009年「數位典藏與數位人文國際研討會」開始，此議題逐漸受到重視，主要目的為將數位文物結合資訊分析與圖像化輔助，透過不同層面的詮釋建構出更完整的文物資訊。 本研究建構一個針對各種中文語料分析的工具，藉由latent semantic analysis、pointwise mutual information、Person’s chi-squared test、typed dependencies distance、word2vec、Gibbs sampling for latent Dirichlet allocation等計算語料中關鍵詞彙關聯強度的方法，並結合分群方法找出可能的主題，最後擷取符合分群結果的相關句子予以輔助人文學者分析詮釋。透過提供各種觀察語料的面向，進而提升語料相關研究學者的效率。 我們利用《人民日報》、《新青年》、《聯合報》、《中國時報》作為實驗與測試的中文語料。且將《新青年》藉由此套工具分析後的結果提供給專業人文學者，做為分析詮釋的參考資訊與佐證依據，並在「2015年數位典藏與數位人文國際研討會」中發表論文。目前我們透過各種中文語料評估工具的效能，且在未來將公開此套工具提供給更多學者使用，節省對於語料分析的時間。 / In recent years, a wide variety of text documents have been transformed into digital format. Hence, using data mining techniques to analyze data is becoming more and more popular in many research fields. The digital humanities gradually have taken seriously since "International Conference of Digital Archives and Digital Humanities" began in 2009. The main purpose of the digital heritage combined with information analysis and visualization could improve the effectiveness of cultural information through different levels of interpretation. In this study, we construct a set of tools for Chinese text mining, calculating associated strengths of collocations work through latent semantic analysis, pointwise mutual information, Person’s chi-squared test, typed dependencies distance, word2vec, and Gibbs sampling for latent Dirichlet allocation etc. The tools employ clustering method to identify the possible topics, meanwhile, the tools will extract the relevant statements according to the clustering results. These clustering and relevant statements contribute and improve the efficiency of humanities scholars’ analysis through providing a variety of observations about the corpora. At the experimental stage of this study, we considered the "People's Daily", "New Youth", "United Daily News", and "China Times" as as the corpora for testing. Among the research, humanities scholars analyzed the "New Youth" by the tools and published a paper in the "2015 International Conference of Digital Archives and Digital Humanities". Currently, we assess the effectiveness of the tools through a variety of Chinese corpora. In the future, we will make the tools freely available on the Internet for Chinese text mining. We hope these time-saving tools can assist in humanities scholars’ study of Chinese corpora.

本論文以兩篇結論對立的社論為個案，藉由形式語義學設計出將論說性篇章刻畫成一階謂詞邏輯符號的論述分析程序，使自然語言中對真實宣稱或正當宣稱的爭論還原成真值語義和論證形式有效性的判斷，從而具體地挽救被歧見所破壞的溝通行動。設計過程初擬了處理語篇命題結構、複合語句成分、回指關係、量號轄域歧義、因果語句、隱性前提推論、和引述結構的實用方案。 / By the means of formal semantics, this thesis used two opposite editorials as cases to design a discourse analysis procedure which translates expository-argumentative texts into formulae of first-order predicate logic. The procedure reduces disputes in natual language about truth or rightness claims into judgements on truth values and validities of argument forms, thus the communicative actions disabled by quarrels can be practically redempted. The designing drafted feasible treatments for propositional structures of discourses, compound sentential constituents, anaphoras, quantifier scope ambiguities, cause-and-effect statements, inferences for absent premises, and quotation structures.

現今由於之前企業併購熱潮，使得企業到底價值多少？企業是否能夠還有前景？這些問題不僅僅是投資者所關心的問題，也同樣是會計師及企業評價者所關心的問題。又現今已邁入知識經濟時代，企業已從過去以土地、廠房、設備等固定資產來產生企業價值，轉而以服務、品牌、專利等無形資產為主要的企業價值時，企業的價值又要如何來估算。而這些問題都一再的顯示出“企業評價”的重要性。 在進行企業評價之前，企業評價模型中之資料項的取得更是關係著最後評價結果的好壞。在企業評價資料項中，可分為財務性及非財務性。財務性資料項由於定義清楚，所以在資料的收集上較非財務性資料容易。但我們發現過往之資料收集方式並不足以應用在企業評價非財務性資料項的收集上，且現行大多採用人工處理資料的方式，不僅耗費大量時間及成本，又因人工輸入而有資料輸入錯誤之風險，使得資料的正確性大幅降低。故本研究提出一自動化擷取年報中企業評價非財務性資料項之方法，希望藉此方法達到簡化資料收集過程，提高資料的正確性。 / Because of the trend of the business combination, now, more and more people concern about “how much value does a business have?” And “does the business still have any perspectives?” This not only get investors’’ interest, but also the accountant and business valuator. Now we already get into a new economy, called knowledge-based economy. When the businesses are not just use fixed asset, such as facility, factory and land to earn money, but also earn their money by providing services, making brand, or sell patents for live, how to measure the business’s real value and what the real value for the business is. These problems all shows that the importance of “Business Valuation.” Before calculate the business value, the most important thing is to collect the data or data category for business valuation. There are two kinds of business valuation data item. One is financial data item; the other is non-financial data item. Because of the financial data item’s clear definition, the data collection process of financial data item is easier than non-financial data item. And the data collection in the past is not fit for today, and now most valuators use manual way to process these data. This way not only wastes the time and money, but also lowers the correctness and raises the risk of mistype during the process of data collection. In this thesis, we propose an approach to automatic extract business valuation data category from annual report by using the technology of data extraction.

本研究旨在探討如何將漢語中詞彙的產出，建構在過去的語言生成模型(speech production model)之上。 在過去文獻中，語言生成模型主要有兩大流派：序列模型(serial-ordering model)主張各階段的激活過程只能單向進行，而連接模型(connectionist model)則允許各階段之間有雙向互動。此外，兩大模型闡述綜合性詞誤 (同時在語意及語音方面相關的詞誤)的生成也略有不同：序列模型認為綜合性詞誤起因於功能層次(functional level)與位置層次(positional level)同時發生錯誤，但若綜合性語誤的比例顯著高於機率，則較不支持此說法；連接模型則認為綜合性詞誤來自音系層(phonological stage)和詞條層(lemma stage)間的交互作用，倘若大部分的縱向聚合詞誤(paradigmatic errors)皆具有語音相似度，此說法較能得到驗證。 因此，為估算漢語詞彙選擇中語音的相似度，本研究分析了421個在自然語境中收集的單音節縱向聚合詞誤，結果發現綜合性語誤所佔的比例顯著偏高，此外，所有詞誤在字首、語音特徵、韻母、音節結構和聲調各方面的效應都達到顯著，這說明了語音和語意的確會同時影響詞彙的選擇，這也表示連接模型可能較接近中文的語言生成過程。 另外，語料分析的結果也顯示出漢語詞彙產出的特性。第一、在詞彙提取的過程中，字首比語音特徵和韻母扮演了更重要的角色，這同時也支持音節結構應以字首(C)和韻母劃分(CV/CVC)的假設；第二、聲調效應的顯著顯示聲調應存在於字彙的底層結構，因此聲調的促發應先於詞彙結的激化；第三、目標詞彙(target)的音節結構應在音系層的初期就已指定，因此有相同音節結構的詞彙結容易勝出。綜合以上可知，漢語的生成過程較傾向連接模型的架構，唯聲調和音節結構等語言特色宜納入模型討論。 / This study aims to investigate the process of word production in Mandarin, to see how it can be structured in previous models. Speech production models have two primary sects—the serial-ordering model versus the connectionist model—arguing for uni-directional and bi-directional activation respectively. Besides, between these two models, the generation of both semantically- and phonologically-related lexical errors (mixed errors) is different. On the one hand, the serial-ordering model (Garrett, 1988) interpreted mixed errors as malfunctions occur at both functional and positional level. It may not be favored if mixed errors occur more than chance in the corpus. On the other hand, the connectionist model (Dell, 1986) explained it as the feedback activation from the phonological level back to the lemma level. It would be supported if most paradigmatic substitutions show phonological similarities. Therefore, in order to facilitate the phonological similarities in lexical substitutions, 421 single-syllable paradigmatic (non-contextual) lexical errors collected in natural settings are examined. It is found that the percentage of mixed errors is significantly higher. Moreover, in the corpus the initialness, similarity, rhyme, syllable structure and tone effects are all prominent, which proves the joint effect of semantic and phonology in word selection. In other words, the connectionist network might better account for the processing of Mandarin. In addition, the analysis reveals certain issues of word-production in Mandarin. First, initials are primary activation units in word retrieval, rather than phonetic features or rhymes. It also supports the division of hierarchical syllable structure as an onset (C) and rhyme (VC/CVC). Secondly, the significance of tone effect suggests that tone may be stored in the underlying phonological organization of lexicons and thus is prior in word-activation. Thirdly, the syllable structure of the target is assigned at the beginning of phonological stage and thus lexical nodes with the same syllable structure tend to be selected. In conclusion, the analysis proves that the connectionist model could be applied to Mandarin Chinese if the status of tone and syllable structure is included.

清代才女左錫嘉有詩詞集《冷吟仙館詩稿》八卷、《冷吟仙館詩餘》一卷。《詩稿》輯錄之詩按時間先後次第排列，且涉及錫嘉事蹟者頗多，所分《浣香小草》、《吟雲集》、《卷葹吟》、《冷吟集》，又正代表著其人生四個重要階段，全書猶如傳記一般。《詩餘》諸詞雖無法斷定是否屬編年形式，但仍具補充《詩稿》之效。故本文乃依上述四集順序，以詩為主、詞為輔，分閨中生活、婚姻生活、跋涉生活、嫠居生活四個時期說明左錫嘉的生平境遇，旨在透過《詩稿》的特殊性質，使錫嘉數十年間的遭際和心路歷程，得到較完整的認識。 　　傳統研究清代女作家，範圍大都僅局限於其個人作品。本文承蒙林師玫儀指導，有了不同以往的論述角度，即是由女作家的家族群體特徵著眼，廣泛蒐羅左錫嘉眾親屬之撰著等資料，就家族成員進行探討，再將所獲相關人事訊息與錫嘉自敘活動經歷之詩詞結合，便可更具體地掌握這類詩詞寫作的時空背景、蘊涵的意念感觸，對錫嘉生平境遇的理解，方能更貼近實情；而錫嘉的各種生命形象、才華、思想及左氏一門的家學淵源，當亦呈現出較清晰的樣貌。

隨著資訊技術的進步，各種史料文本的數位化工作已經處理完成，運用資訊技術於史料文本分析的研究日益增加。本研究以詞頻分析與社會網路分析為主軸，對於古代《易經》爻辭的文字進行多元化的觀察，本研究首先以詞頻分析探討《易經》爻辭字詞頻率的觀察，再利用《易經》爻辭位置資訊建構成各個社會網路結構，對每個社會網路結構運算各項社會網路指標數據，最後將實驗結果與過往《易經》爻辭的論點做印證與對照，期望對於《易經》爻辭之分析，有更多元性的客觀研究觀察。本研究提供了一個分析《易經》爻辭的新面向，也可供未來研究者對於其他古文研究作參考。 / With advances in information technology, digitization of various historical text has been completed.The study of historical text analysis by using information technology is in-creasing daily.In this paper, we used word frequency analysis and social network analy-sis in the I-Ching line statements.First, we used word frequency analysis in I-Ching line statements,using N-gram and TF-IDF technique analysis word frequency.Second, we constructed social network structure by I-Ching line statements position infor-mation,calculating several social network analysis indicator on each network.We com-pared our experiment results with some existing I-Ching theory, expecting to get more objective results and more diverse analysis for the I-Ching line statements. We not only provided a new perspective to study I-Ching line statements but also expected to help other researchers to study different historical text.

華語流行歌詞一直是語言、文學、音樂或是文化研究等相關科系赤手可熱的研究題目，內容包含作詞者、修辭分析、風格、用韻及語言表達等，然由於歌詞數量龐大，難以全部以人工分析。 近年來，資訊科技日新月異不斷地進步，隨著Big Data議題受到注目，Data Mining在近年來相當熱門，然而針對華語流行歌詞的巨量資料探勘與分析研究並不多。因此，本論文研究以程式來自動化分析歌詞的樣式與特性，包括詞彙頻率、詞彙相鄰關係分析、歌名分析、使用語系分析、舊曲新唱、歌詞風格自動分類、用韻及修辭等，而研究資料係透過網路擷取知名網站內容，包含魔鏡歌詞網 (Mojim.com)、臺北之音HitFM聯播網 (www.hitoradio.com) 及教育部重編國語辭典，透過分析規則及以Non-Trivial Repeating Pattern等方法，來完成分析及系統實作。 透過華語流行歌詞的大量分析，探勘及了解各種歌詞的風格與特性，將可了解各種歌詞、作詞者的風格與特色，進而應用在歌詞資料的管理與查詢。 此外，本研究將八萬多首歌詞的各種分析資料設置成網站，提供予學術研究使用，希冀此研究資料能使華語流行歌詞相關研究研究，進行更深入地探討。 / Chinese popular music lyrics has been a popular topic for researchers who major in languages and literature, music or culture. Related studies include of lyricists, rhetoric methods, styles, rhyme and language expression. However, all these studies were performed by manual analysis. It is difficult to analyze large amount of lyrics manually. With advances in computer technology, big data and data mining techniques have been widely used in different kinds of data. However, to the best of our knowledge, none have been done on pattern mining from big data of lyrics of Chinese popular music. Therefore, the objective of this thesis is to discover patterns from tremendous lyrics data based on data mining techniques. We use data downloaded from www.mojim.com, http://dict.revised.moe.edu.tw/cbdic/ and http://www.hitoradio.com (Hit FM). Data mining methods are employed to find lyrics’ patterns and features, including frequent words, word adjacency, analysis of hit songs' names, lyrics’ language studies, cover song research, automatic style prediction, rhyme and rhetoric patterns. With the analysis of tremendous lyrics and data, the developed approaches of this thesis will be helpful for discovering distinguishing styles of lyrics and lyricists.

漢字之使用，歷經時間推移和人為因素之影響，始漸定俗成。漢字包含正體書寫及異體書寫之字，一般稱作正體字及異體字。本文異體字的定義，為同音、同義，字形相異，相對於正體字而言的文字，稱其為異體字。 異體字之產生，在使用文字的過程，或因人為因素、書寫工具、書寫載體，或行草隸變之書體演變等，都可能影響使書寫文字產生變化，即形成所謂的異體字。異體字較籠統的說法，意指相對於正體字而言的漢字。正體字，指官方所頒布，對於一字或有的諸種寫法，採取標準加以製定出一正寫的文字，謂之正體字。漢字在正體字之外，存在更大使用比例的異體字，漢字若缺乏對於異體字之觀點，則對於漢字整體研究而言恐將偏漏不全。 1967年於上海嘉定宣姓婦人墓葬出土一批明代成化年間之說唱文學作品，這批作品出土之前未經著錄，此就在文獻研究價值而言。北京文物出版社1979年影印刊行，以俾便學界研閱之參考。這批作品以其斷代明確且保存異體字豐富，備受關注，此文本異體字形變化多元豐富，筆者以疏理其異體字形，進行本文明成化說唱詞話異體字研究，完成《說唱詞話》異體字之分析，包括異體字之簡化、繁化、同化、異化等類型，詳見本文第2章至第5章，異體細部字形之變化，於各章分節中列舉字例加以闡述，綱舉目張以簡御繁，以清眉目，第6章以異體字類型為基礎，加以綜論凸顯《說唱詞話》異體字之特徵，終一章略以餘論為結，完成本文明成化說唱詞話異體字之研究。 漢文字歷經漫長的歷史過程，其間待研究之內涵浩如煙海，未來更整全之漢字史之呈現，期待更多學人同好加入研究傳承的行列，漢字為今日唯一留存完整的象形文字，為人類瑰寶，尤其值得我們漢字使用者多加利用並傳承之。