主題-評論結構(topic-comment)在主題顯著(topic prominent)的語言(如中文)扮演十分重要的角色,尤其是在描述第二語言學習者的中介語時特別重要．但是有關研究,對於中國學生在學習英文時產生的中介語,並沒有對主題-評論結構提供全面且確切的描述．本研究旨在探討中國學生學習英文時所產生的中介語之主題-評論結構, 運用三種測驗來引出中介語—文法判定測驗, 引導寫作測驗, 及翻譯測驗．受試者包含台灣區域位於台北的三所國中挑選的94位國二生,以國一期末考英文成績分為三組．此外,並於政大語視中心挑選14位以英語為母語的外籍生作為本研究的控制組．本研究探討的四種主題-評論結構是由中英文主題結構對比中所產生的, 分別為主題省略(topic drop), 主題移前(topicalization), 主題置左(left-dislocation), 及雙主詞結構(double-subject construction)．本研究所運用的中介語之理論架構是參考三種第二外語習得理論所發展出來的, 分別為第一語言影響(L1 influence), 普遍語法(universal grammar)的存在, 以及附屬集合理論(the Subset Principle)． 研究結果顯示, 第一語言轉換(L1 transfer)在所有程度的學生的中介語當中都十分普遍, 但是普遍語法只有在程度最高的學生的中介語較為明顯．因此本研究推論中介語系統內部運作過程包含三階段, 開始為第一語言轉換, 接著是第一語言轉換及普遍語法並存, 最後階段為普遍語法． / The role that the topic-comment structure plays in a topic prominent language such as Chinese is very important when it comes to SLA learners’ interlanguage. However, the related research has not provided a comprehensive framework in describing topic structures of Chinese EFL learners’ interlanguage. The purpose of this study is to analyze the topic structures in Chinese EFL learners’ interlanguage elicited by three tasks—the grammaticality judgment task, the guided writing task, and the translation task. The subjects include 94 junior high school students chosen from three separate schools in Taipei, Taiwan, and they were divided into three proficiency levels. In addition, 14 native speakers from the language center of NCCU served as the control group. This study investigated four topic structures—topic drop, topicalization, left-dislocation, and double-subject construction—which were determined by a comparative study of Chinese and English topic structures. The current theoretical framework of interlanguage operation is developed from three SLA perspectives—L1 influence, the existence of universal grammar (UG), and the subset principle. Results indicated that L1 transfer was prevalent in all proficiency levels but UG was only obvious in the most advanced level. It was thus inferred that the internal operation of interlanguage system should include three stages—first L1 transfer, then L1 transfer and UG, and finally UG.

句子的主題具備了串連訊息、引導文句發展的重要功能，然而資料顯示許多外語學習者常因為使用不適當的主題而影響語句的連貫性以及文章的流暢度。本研究透過觀察台灣高中生記敘文的主題類型，分析其在高、中、低分群學生文章中的使用情形來了解主題的選用對文章連貫性以及整體作文品質的影響。 本研究分成初步試驗以及正式研究兩階段，在初步試驗階段我們建立了分析的架構。在正式研究階段，我們採集111位高三學生於課堂上完成的記敘文並交由兩位經過訓練的閱卷老師進行評分，最後結果產生高、中、低分三組學生作文，接著再從每一組的文章中各抽樣10份進行主題類型之分析研究。 分析結果顯示，三組學生作文的主題類型及出現頻率大致雷同，整體而言，學生最喜好使用非標記的名詞主題，卻最少使用標記的分詞+名詞主題。然而進一步分析三組的主題發展情形，卻發現有顯著的組別差異，以高分群為例，其主題多具備銜接上文或有利推進文意的背景資料文字，相較之下，中等或低分群的作文比較容易出現和上下文不相關或中斷文意發展的新主題。 根據本研究的發現，我們建議在英語作文課中介紹句子主題的概念，幫助學生熟悉其類型和功能，期使學生能在記敘文文章中正確使用主題來達到語句連貫，文意流暢的溝通目標。 / Theme plays a significant role in guiding the information flow in text. Nonetheless, there is evidence indicating that many EFL learners often fail to make good choices of theme to secure sentential relationship or writing coherence. Through the observation on the occurrences and distribution of theme types in three levels of student compositions: the high, the middle and the low-rated narratives, the present study aims to investigate the establishment of theme in Taiwanese senior high school students’ narratives in order to gain understanding of theme’s effect on writing coherence and writing quality. The entire study consists of a pilot study and a formal one. The pilot study helps establish the criteria for the main study. In the main study, 111 student compositions were gathered and two raters were recruited and trained for the rating. Based on the rating system, the student compositions are divided into 3 levels. 10 samples from each level were randomly selected for thematic analysis. The result shows that the occurrences and distribution of theme types in the three levels of writing are alike. In general, unmarked NP theme is the most favored by all the students and marked theme Non-fi C + NP is the least desirable. Nonetheless, in terms of the establishment of theme, there are major differences between groups. In particular, the high-rated essays tend to establish a theme that is connected to the theme or the rheme in the preceding discourse or provides background information for the development of the event. In contrast, the mid-or low-rated essays are more likely to establish a theme that is unrelated or disruptive to the progression of the current discourse. Based on the findings of the present study, it is suggested that the notion of theme including its features and functions be incorporated into the teaching of English compositions to help Taiwanese senior high school students identify the characteristics of coherent writing and facilitate coherence in their English narratives.

No description available.

由於網際網路的普及造成資訊量愈來愈大，在資訊的搜尋、整理與閱讀上會耗費許多時間，因此本研究提出一應用文本主題及關係探勘的方法，將多份文件自動生成一篇摘要，以幫助使用者能降低資訊的閱讀時間，並能快速理解文件所欲表達之意涵。 本研究以電影評論文章為例，結合文章結構的概念，將影評摘要分為「電影資訊」、「電影劇情介紹」及「心得結論」三部分，其中「電影資訊」及「心得結論」為透過本研究建置之電影領域相關詞庫比對得出。接著將餘下之段落歸屬於「電影劇情介紹」，並透過LDA主題模型將段落分群，再運用主題關係地圖的概念挑選各群之代表段落並排序，最後將各段落去除連接詞及將代名詞還原為其所指之主詞，以形成一篇列點式影評摘要。 研究結果顯示，本研究所實驗之三部電影，產生之摘要能涵蓋較多的資訊內容，提升了摘要之多樣性，在與最佳範本摘要的相似度比對上，分別提升了10.8228%、14.0123%及25.8142%，可知本研究方法能有效掌握文件之重點內容，生成之摘要更為全面，藉由此方法讓使用者自動彙整電影評論文章，以生成一精簡之摘要，幫助使用者節省其在資訊的搜尋及閱讀的時間，以便能快速了解相關電影之資訊及評論。 / The rapid development of information technology over the past decades has dramatically increased the amount of online information. Because of the time-wasting on absorbing large amounts of information for users, we would like to present a method in this thesis by using text topic and relationship mining for multi-document summarization to help users grasp the theme of multiple documents quickly and easily by reading the accurate summary without reading the whole documents. We use movie reviews as an example of multi-document summarization and apply the concept of article structures to categorize summary into film data, film orientation and conclusion by comparing the thesaurus of movie review field built by this thesis. Then we cluster the paragraphs in the structure of film orientation into different topics by Latent Dirichlet Allocation (LDA). Next, we apply the concept of text relationship map, a network of paragraphs and the node in the network referring to a paragraph and an edge indicating that the corresponding paragraphs are related to each other, to extract the most important paragraph in each topic and order them. Finally, we remove conjunctions and replace pronouns with the name it indicates in each extracted paragraph s and generate a bullet-point summary. From the result, the summary produced by this thesis can cover different topics of contents and improve the diversity of the summary. The similarities compared with the produced summaries and the best-sample summaries raise of 10.8228%, 14.0123% and 25.8142% respectively. The method presented in this thesis grasps the key contents effectively and generates a comprehensive summary. By providing this method, we try to let users aggregate the movie reviews automatically and generate a simplified summary to help them reduce the time in searching and reading articles.

隨著Web 2.0興起，社群網站在資訊傳遞與獲取所占比重相當高。以美食領域來看，人們在進餐廳前先行閱覽食記評論之情形越來越常見，而部落格文章因圖文並茂，常被消費者列入參考比較之來源。儘管這一類食記內容相對短篇食評來說較為完整，但評論分散於文章中，且多半沒有評分可供參考，讀者很難在第一時間獲悉評論樣貌，得花上一番心力進行閱覽，才能對餐廳整體有所評鑑。 本研究提出一套基於意見探勘與主題模型的食記剖析方法，由部落格中各餐廳貼文情緒量來反映正負面評價，將提及評論歸納為「食物」、「服務」及「環境」三個評分面向，進而提供該家餐廳的整體推薦分數，供讀者快速參閱之。實驗語料自痞客邦美食類貼文中選定添好運台灣－台北站前店、京星港式飲茶PART2、金泰日式料理－內湖店以及喀佈貍（一店）大眾和風串燒居酒洋食堂，合計4家餐廳與200篇語料。 透過LDA主題模型對食記敘述進行主題式分群，使擁有相近主題概念的句子分為一群，並歸類至各面向，例如喀佈貍（一店）之語料可分為10群主題語句，食物面向上有6群，服務與環境面向各為2群。另一方面，為了更有效辨別食記中含有的正負向情緒，本研究透過語意導向方法(SO-PMI)來計算食記中常出現情緒詞彙之極性，以建置該領域的意見詞詞庫。 實驗結果方面，以線上餐廳評論網站－iPeen愛評網作為驗證對象，顯示其語料的平均情緒量相近，於大眾觀感與評價上傾向一致，且相較一般評論網站，本研究能從較細微的面向來切入，並以情緒量反映真實的餐廳評價。最後提出未來欲探討與改善之處，供後續研究參考之。 / As the time of Web 2.0 rise, social media platform plays a crucial role in transferring and receiving information. More and more people get used to reading the related posts before having meal. Because of its richness in content and referring photographs, blog posts are most frequently used for reference. Although the blog posts are more complete regarding their content than other short reviews, the actual reviews are scattered among words that are simply descriptions, and there are no grading scale to take as reference. These all together gives the reader a hard time to efficiently organize the overview of the review, and for them to, therefore, make the decision if they should go to the restaurant. Our study offers a method of analyzing food diaries based on opinion mining and topic model. The scale of emotion in a blog post about a restaurant is used as the reflection of its review's positive or negative. The comments are categorized into food, service and environment. And the restaurant will be graded based on these three aspects to further provide the user an overall score of recommendation. We collected total of 200 articles written on 4 restaurants in PIXNET, then categorized the contents using LDA (Latent Dirichlet Allocation) model base on their theme. The sentences with similar theme with be put into a group, then be further categorized to the three aspects that was mentioned earlier. On the other hand, to better distinguish if the emotion in certain food diary is positive or negative, our study calculated the polarity of common opinion-based words in food diaries using semantic orientation (SO-PMI), and built an opinion corpus specifically for food diaries. In terms of the result, using iPeen, a restaurant rating website, as test reference, it shows that the average scales of opinion of the restaurants we got using our method are close to iPeen, which in this case we can say are close to the public opinion and review. Furthermore, compare to common rating website, our study touches on even the minute aspect, and use the cumulative opinion to reflect the true blog authors' evaluation of the restaurant. Lastly, we would like to bring up what we intend to discuss and improve in the future for upcoming research's reference.

在現在的社會裡，手機應用程式已經被人們接受與廣泛地利用，然而目前市面上的手機 App 推薦系統，多以使用者實際使用與回報作為參考，若有惡意行為軟體，在使用者介面後竊取使用者資料，這些推薦系統是難以查知其行為的，因此我們提出了 AppReco，一套可以系統化的推薦 iOS App 的推薦系統，而且不需要使用者去實際操作、執行 App。 整個分析流程包括三個步驟：(1) 透過無監督式學習法的隱含狄利克雷分布(Latent Dirichlet Allocation, LDA)做出主題模型，再使用增長層級式自我組織映射圖(Growing Hierarchical Self-Organizing Map, GHSOM)進行分群。(2)使用靜態分析程式碼，去找出其應用程式所執行的行為。(3)透過我們的評分公式對於這些 App，進行評分。 在分群 App 方面，AppReco 使用這些應用程式的官方敘述來進行分群，讓擁有類似屬性的手機應用程式群聚在一起；在檢視 App 方面，AppReco 透過靜態分析這些 App 的程式碼，來計算其使用行為的多寡；在推薦 App 方面，AppReco 分析類似屬性的 App 與其執行的行為，最後推薦使用者使用較少敏感行為(如使用廣告、使用個人資料、使用社群軟體開發包等)的 App。 而本研究使用在 Apple App Store 上面數千個在各個類別中的前兩百名 App 做為我們的實驗資料集來進行實驗。 / Mobile applications have been widely used in life and become dominant software applications nowadays. However there are lack of systematic recommendation systems that can be leveraged in advance without users’ evaluations. We present AppReco, a systematic recommendation system of iOS mobile applications that can evaluate mobile applications without executions. AppReco evaluates apps that have similar interests with static binary analysis, revealing their behaviors according to the embedded functions in the executable. The analysis consists of three stages: (1) unsupervised learning on app descriptions with Latent Dirichlet Allocation for topic discovery and Growing Hierarchical Self-organizing Maps for hierarchical clustering, (2) static binary analysis on executables to discover embedded system calls and (3) ranking common-topic applications from their matched behavior patterns. To find apps that have similar interests, AppReco discovers (unsupervised) topics in official descriptions and clusters apps that have common topics as similar-interest apps. To evaluate apps, AppReco adopts static binary analysis on their executables to count invoked system calls and reveal embedded functions. To recommend apps, AppReco analyzes similar-interest apps with their behaviors of executables, and recommend apps that have less sensitive behaviors such as commercial advertisements, privacy information access, and internet connections, to users. We report our analysis against thousands of iOS apps in the Apple app store including most of the listed top 200 applications in each category.

本論文以「詞彙功能語法」來分析中文「移位矛盾」之現象，以Bresnan (2001)針對英文movement paradoxes以及Huang (1989)，Her (1999)針對中文「移位矛盾」之研究為基礎，探討當述語所要求的典型的「名詞組賓語」被禁止出現時，將藉由體現為主題來滿足述語對賓語的要求，但並不是所有詞類的賓語都可以體現為滿足述語要求的主題。因此，本論文將中文中帶有移位矛盾現象的述語分為三大類，蒐集並分析這三大類述語在語料庫中的語料，將得以呈現只有名詞組、動詞組、句子以及帶有引介主題標記的介系詞組可以體現為主題。本論文更進一步為可以體現為主題的詞組建立一個階層，在此階層中位階最高的是名詞組，代表著名詞組在體現為帶有移位矛盾現象的述語之主題時，所受到的限制最小。除此之外，這個階層帶有遞移性，任一詞組若是可以體現為主題，則在階層中位階比該詞組高的詞組，也都可以體現為該述語的主題，反之則不一定成立。 / Based on Bresnan’s (2001) study of movement paradoxes in English and Huang’s (1989) and Her’s (1999) studies of movement paradoxes in Mandarin Chinese, this study discusses that when the prototypical NP object required by the predicate is forbidden to map to the OBJ function in the f-structure, this required NP argument must be realized as TOP identified with the missing OBJ to satisfy the Completeness and Coherence Conditions. However, not all category types of phrases can be realized as TOPs. Thus, this study classes the Mandarin Chinese predicates with movement paradoxes into three types; collect and analyze the data in the corpus. The analysis presents that only NP, VP, CP, and PP with topic-introducing marker can be realized as TOPs identified with the missing OBJ. Moreover, this study forms a hierarchy. The NP’s highest status in this hierarchy represents that it is the least restricted category type in being able to be realized as TOP of predicates with movement paradoxes. In addition, if one category type can be realized as TOP of one predicate, other category types with a higher priority can be realized as TOP of that predicate as well, but not vice versa.

This study is thematic analysis that sought to identify nationalistic themes in mainland China's box-office hits in the 21st century. Box-office hits as the study material were picked because of their potential to spread the message they carry. Altogether, 14 movies were analyzed through a deconstruction, identifying scenes and dialogues that contained nationalistic appeals of both political and cultural nationalism as defined by Greenfeld (1992). During the coding process, 22 nationalistic themes were labeled, defined and described. Additionally, the study examined nationalistic structures of the movies taking Gries' (2004) nationalistic narratives and Smith's (1995) ethnic myths as a basis. Movies' background, and historical context adressing China's movie industry and Chinese nationalism are included for clarification purposes. The movies were found to exhibit manifestations of both cultural and political nationalism. It was found that movies financed and backed by government tend to show political nationalism while commercial movies exhibit cultural nationalism. For the movies' thematic structures, the shift from positive ones showing China's achievements towards negative ones expressing China's suffering was discovered. / This study is thematic analysis that sought to identify nationalistic themes in mainland China's box-office hits in the 21st century. Box-office hits as the study material were picked because of their potential to spread the message they carry. Altogether, 14 movies were analyzed through a deconstruction, identifying scenes and dialogues that contained nationalistic appeals of both political and cultural nationalism as defined by Greenfeld (1992). During the coding process, 22 nationalistic themes were labeled, defined and described. Additionally, the study examined nationalistic structures of the movies taking Gries' (2004) nationalistic narratives and Smith's (1995) ethnic myths as a basis. Movies' background, and historical context adressing China's movie industry and Chinese nationalism are included for clarification purposes. The movies were found to exhibit manifestations of both cultural and political nationalism. It was found that movies financed and backed by government tend to show political nationalism while commercial movies exhibit cultural nationalism. For the movies' thematic structures, the shift from positive ones showing China's achievements towards negative ones expressing China's suffering was discovered.

隨著經濟發展，工業化成熟，台灣的產業結構正逐漸由「製造的台灣」(Made in Taiwan)轉型為「服務的台灣」(Served by Taiwan)。我國休閒旅館業為了能夠提升競爭力，近年來積極發展服務創新，希望透過創新方式來提高競爭門檻，避免價格戰，提高品牌與服務價值。但創新人人會談，問題是怎麼做？每間旅館飯店在發展服務創新時，乃是依據不同的策略思維，由於本身營運模式的營運範疇、核心資源及事業網路不同，建構出不同服務創新的模式。 回顧過去文獻探討，服務創新應用在休閒旅館業之研究，此新興議題乃付之闕如，且大多探討服務創新的內涵與構面之間關係，但卻鮮少深入分析服務創新背後的策略構面與服務創新模式的關聯性，故本研究參考吳思華所提之「策略三構面」及Bilderbeek & Hertog所提出之「服務創新四構面」作為本研究之研究架構，並以悠活麗緻渡假村之「兒童旅館」、「單車旅館」與「樂活長住U化全心服務建置計畫」為例，運用個案研究法並輔以次級資料之搜集與整理，詳細剖析其公司經營模式，如何建構出其專屬的服務創新模式與內涵。 本研究獲得以下主要結論： 1.公司「營運範疇」之「產品市場」與「地理構形」，可能會影響創新概念的產生，並透過調整「活動組合」，可以提升產品價值與差異化特色。 2.公司「核心資源」之「經營團隊」，有助於建立良好「事業網路」關係，可產生與策略夥伴合作的機會。 3.公司「技術選擇」有時為創新服務模式的重要成功因子，且運用於設計「客戶介面」與「服務傳遞系統」。 4.公司若本身財務資源不足時，有時可透過創新且特殊的服務概念，帶來行銷宣傳效益。 5.公司欲往「提升價值」發展時，可透過「技術選擇」來提升效率，並整合其既有策略構面，可以維持競爭優勢。 本研究之建議如下： 1.組織發展服務創新模式前，應基於其公司的策略構面與整體經營模式，而規劃出適合的服務創新模式。 2.休閒旅館進行服務創新時，若欲透過資訊科技來提供加值服務時，可運用外部的資源。 3.休閒旅館在發展主題式概念旅館時，需要注意「跨越鴻溝」之問題。

本研究目的在於結合關聯規則新詞發掘演算法來擴增詞庫，並藉此提高結斷詞句的精確度以及透過非監督式情感分析方法，從中央通訊社中抓取國民黨以及民進黨的相關新聞文本，建立主題模型與情緒傾向的標注。再藉由監督式學習方法建立分類模型並驗證其成果。 　　本研究藉由n-gram with a-priori algorithm來進行斷詞斷句的詞庫擴增。共有32007組詞被發掘，於這些詞中具有真正意義的詞共有28838筆，成功率可達88%。 　　本研究比較兩種分群方法建立主題模型，分別為TFIDF-Kmeans以及LDA。在TFIDF-Kmeans分群結果中，因為文本數量遠大於議題詞數量，造成TFIDF矩陣過於稀疏，造成分群效果不佳。在LDA的分群結果底下，因為LDA模型其多文章多主題共享的特性，主題分類的精準度更高達八成以上。故本研究認為在分析具有多主題特性之文本，採用LDA模型來進行議題詞分群會有較佳的表現。 　　本研究透過結合不同的資料時間區間，呈現出中央通訊社的新聞文本在我國近五次總統大選前後三個月間的新聞情緒傾向。同時探討各主題模型中各類別於大選前後三個月之情緒傾向變化。可以觀察到大致上文本的情感指數高峰值會出現於投票日的時候，而近三次總統大選的結果顯示，相關的政黨新聞情感值會於選舉過後趨於平緩。而從新聞文本的正負向情感統計以及以及整體情緒傾向分析可以看出，不論執政黨為何，中央通訊社的新聞對於國民黨以及民進黨皆呈現了正向且平穩的內容，大抵不會特別偏向單一政黨 / The purpose of this research is to combine association rules and new word mining algorithms to expand the lexicons so as to improve the accuracy of word segmentations, and by capturing the KMT and DPP news from the Central News Agency, it establishes the theme model and sentiment orientation through the unsupervised sentiment analysis method. Finally, by means of supervised learning methods, this research establishes classifications models and verifies its results. 　　This research uses n-gram with a-priori algorithm to segment words and sentences to expand the lexicons. A total of 32007 word are found, and among them, there have 28838 words with real meaning. The success rate is up to 88%. 　　In this research, we compare two different clustering methods to form the theme model, which are the TFIDF-Kmeans, and the LDA. From the results of TFIDF-Kmeans, the TFIDF matrix is too sparse, resulting in poor clustering because the number of texts is a lot larger than that of the issues. Unlike TFIDF-Kmeans, because of LDA model with more features of multi-topic sharing, the accuracy of topic classification is more than 80%. Therefore, this research suggests that it will have a better performance to analyze the multi-subjective texts with LDA model to classify the word clustering. 　　Through the combination of different data time interval, this research presents the sentimental tendencies of Central News Agency’s news in three months before and after the last five presidential elections in Taiwan. At the same time, it also explores the changes of the sentimental tendencies in the various theme models in the three months before and after the election. It can be observed the sentimental peak of the text will be appeared on the polling day, and nearly three times of the presidential election results show that the sentimental value of the relevant party’s news will become smooth after the election. From the positive and negative sentimental statistics of the news text and the analysis of the overall sentimental tendencies, no matter which the ruling party is, the news of the Central News Agency for the KMT and the DPP presents a positive and stable content, not particularly toward any political party.