**Curriculum Vitae (中文), update: 20180327**

# **Curriculum Vitae (中文), update: 20180327** ## **傅昱翔 (Fu, Yu-Hsiang)** 我是傅昱翔，熱衷於使用Python程式語言及撰寫電腦模擬程式，隨後應用在分析複雜網絡、社會網絡及演化式計算等研究問題上，目前正朝著成為大數據分析、資料科學、人工智慧與深度學習等領域專家的方向前進。 ### **聯絡方式** * b9109045@hotmail.com * yuhsiang.fu@gmail.com ### **個人頁面** * https://www.linkedin.com/in/yuhsiangfu/ * https://www.gitbook.com/@yuhsiangfu * https://github.com/yuhsiangfu * [Google Scholar](https://scholar.google.com/citations?user=TchKuoQAAAAJ&hl=en) ### **學習經歷 (Education)** * 2010/02 ~ 2018/07：國立交通大學資訊科學與工程研究所博士班 * 2008/09 ~ 2009/09：日本会津大學 (University of Aizu) 交換學生 * 2006/09 ~ 2010/01：朝陽科技大學資訊管理所碩士班 * 2002/09 ~ 2006/06：嘉南藥理科技大學資訊管理系 ### **研究領域 (Research Fields)** * [複雜網絡理論](https://en.wikipedia.org/wiki/Complex_network) (complex network theory) * [社會網絡分析](https://en.wikipedia.org/wiki/Social_network_analysis) (social network analysis) * [電腦模擬](https://en.wikipedia.org/wiki/Computer_simulation) (computer simulation) * [演化式計算](https://en.wikipedia.org/wiki/Evolutionary_computation) (evolutionay computation) * [網站使用探勘](https://en.wikipedia.org/wiki/Web_mining#Web_usage_mining) (web usage mining) ### **興趣領域 (Interested Fields)** * 人工智慧、[遊戲人工智慧](https://en.wikipedia.org/wiki/Artificial_intelligence_(video_games))、[群體智慧](https://en.wikipedia.org/wiki/Swarm_intelligence)、[人工生命](https://en.wikipedia.org/wiki/Artificial_life) * 深度學習、類神經網路 * 資料探勘、網站探勘、[地理資訊探勘](https://en.wikipedia.org/wiki/Geographic_information_system) * 電腦視覺、影像處理、[眼動追蹤](https://en.wikipedia.org/wiki/Eye_tracking) ### **獲獎記錄 (Awards)** * 2017/02：[Certificated Reviewer of Physica A: Statistical Mechanics and its Applications~[pic]~](https://drive.google.com/open?id=1_MAQQYcr-__zNkle6iutWRWnx6a1LTxW) * 2016/04：[ICIAE 2016 國際研討會, Best Student Paper Award~[pic]~](https://drive.google.com/open?id=1oIBux3iLMjZnRmt46p2MFVpjrx82nji1) * 2007/09：[96年度教育部學海惜珠計畫~[pdf]~](https://drive.google.com/open?id=1uXcVrVhzG3EQwavTWvO-TXxrX1RNR_i3) ### **程式技能 (Programming Skills)** * 2013 ~ Now：[Python](https://www.python.org/), [Cython](http://cython.readthedocs.io/en/latest/index.html), [NumPy](http://www.numpy.org/), [SciPy](https://www.scipy.org/), [NetworkX](https://networkx.github.io/), [Matplotlib](https://matplotlib.org/) * 2010 ~ 2012：C, Java, Excel * 2007 ~ 2009：HTML, CSS, Java, Excel * 2002 ~ 2006：ASP, ASP.NET, VB.NET, PHP, C, C++. ## **專題與報告 (Selected Projects & Reports)** ### **服役時期 (Military Service)** 在服役期間，利用空閒時間自學網路爬蟲及文章斷詞等技術，透過撰寫小型專題來整合所學技術，同時在Gitbook上撰寫一本Python程式設計與資料分析的線上著作。 * [基礎程式設計與資料分析~[gitbook]~](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/) * [基礎程式設計](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/short-1-ji-chu-cheng-shi-she-ji.html) * 介紹Python程式語法及資料結構 * 基礎演算法 * 介紹[排序](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/class-a1-pai-xu-yu-sou-xun/a11-cha-ru-pai-xu-fa.html)、[搜尋](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/class-a1-pai-xu-yu-sou-xun/a12-er-yuan-sou-xun-fa.html)、[遞迴](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/a21-di-hui.html)及[分治法](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/a22-kuai-su-pai-xu.html) * 基礎資料蒐集 * 介紹[網站爬蟲](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-1-zi-liao-sou-ji-wang-zhan-pa-chong.html)及[Facebook社群網站爬蟲](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-2-zi-liao-sou-ji-she-qun-wang-zhan-pa-chong.html) * [基礎資料分析](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-3-zi-liao-fen-xi-k-means-fen-qun.html) * 介紹[K-means分群](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-3-zi-liao-fen-xi-k-means-fen-qun.html)、[K-Nearest Neighbor分類](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-4-zi-liao-fen-xi-k-nearest-neighbor-fen-lei.html)、[社會網絡分析](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-5-zi-liao-fen-xi-she-hui-wang-luo-fen-67902c-jie-dian-zhong-yao-xing-fen-xi.html)及[社會網絡分群](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/content/analysis-6-zi-liao-fen-xi-she-hui-wang-luo-fen-67902c-wang-luo-jie-dian-fen-qun.html) * [News Analysis~[github]~](https://github.com/yuhsiangfu/news-analysis) * [新聞爬蟲~[code]~](https://github.com/yuhsiangfu/news-analysis/blob/master/chinatimes_crawler.py) * 先利用[Requests](http://docs.python-requests.org/en/master/)連線至[中時電子報網站](http://www.chinatimes.com/)，再使用[BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/)分析新聞網頁的HTML結構及擷取出新聞的文字內容，最後取得某特定主題近期內所有的新聞內容。 * [文章斷詞~[code]~](https://github.com/yuhsiangfu/news-analysis/blob/master/word_segmentation.py) * 使用[jieba](https://github.com/ldkrsi/jieba-zh_TW)套件對每則新聞的文字內容做斷詞處理。 * [字詞視覺化~[code]~](https://github.com/yuhsiangfu/news-analysis/blob/master/latent_semantic_analysis.py) * 先利用Numpy建立[字詞-文件(Term-Doc, TD)矩陣](https://en.wikipedia.org/wiki/Document-term_matrix)，再使用[奇異值分解(SVD)](https://en.wikipedia.org/wiki/Singular-value_decomposition)或主成份分析(PCA)對TD矩陣進行降維及去除雜訊，接者透過[scikit-learn](http://scikit-learn.org/)中[流形學習](http://scikit-learn.org/stable/modules/manifold.html)的[t-SNE](http://scikit-learn.org/stable/modules/manifold.html#t-distributed-stochastic-neighbor-embedding-t-sne)方法對降維後的TD矩陣做[字詞視覺化~[pic]~](https://github.com/yuhsiangfu/news-analysis/blob/master/latent_space.png)。 ### **博士班時期 (Doctoral Program)** 在博士班期間，自學Python程式語言，主要目的是要撰寫複雜網絡、電腦模擬及演化式計算等研究領域的實驗程式，同時透過資料視覺化的方式呈現資料分析與模擬實驗的結果。 * [複雜網絡的滲流模擬~[github]~](https://github.com/yuhsiangfu/network-percolation) * [生成理論網絡~[code]~](https://github.com/yuhsiangfu/network-percolation/blob/master/theoretical_network_generator.py) * 產生正規網絡、隨機網絡、無尺度(scale-free)網絡及小世界網絡等四種理論網絡 * [滲流模擬~[code]~](https://github.com/yuhsiangfu/network-percolation/blob/master/network_percolation.py) * 在理論網絡上做[滲流(percolation)](https://en.wikipedia.org/wiki/Percolation_theory)模擬 * [滲流模擬的視覺化~[code]~](https://github.com/yuhsiangfu/network-percolation/blob/master/figure_network_percolation.py) * 產生滲流模擬結果的曲線圖[~[bond-pic]~](https://github.com/yuhsiangfu/network-percolation/blob/master/image/network-percolation-bond%2C%20sim%3D100.png)[~[site-pic]~](https://github.com/yuhsiangfu/network-percolation/blob/master/image/network-percolation-site%2C%20sim%3D100.png) * [複雜網絡的擴散模擬~[github]~](https://github.com/yuhsiangfu/network-spreading) * 生成理論網絡 * [網絡分析~[code]~](https://github.com/yuhsiangfu/network-spreading/blob/master/network_analysis.py) * 使用[中心性(centrality)](https://en.wikipedia.org/wiki/Centrality)方法衡量理論網絡中各個節點的中心性 * [擴散模擬~[code]~](https://github.com/yuhsiangfu/network-spreading/blob/master/network_spreading.py) * 以中心性最高的節點做為初始節點，利用[SIR傳染病模型](https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIR_model)在理論網絡上做[擴散](https://en.wikipedia.org/wiki/Rumor_spread_in_social_network)模擬 * [擴散模擬視覺化~[code]~](https://github.com/yuhsiangfu/network-spreading/blob/master/figure_network-spreading.py) * 產生網絡擴散結果的曲線圖[~[隨機網絡-pic]~](https://github.com/yuhsiangfu/network-spreading/blob/master/image/random_n%3D1000_k%3D5%2C%20spreading-r0%3D1.5-topk%3D1-sim%3D100-t%3D50.png)[~[無尺度網絡-pic]~](https://github.com/yuhsiangfu/network-spreading/blob/master/image/ba_n%3D1000_k%3D5%2C%20spreading-r0%3D1.5-topk%3D1-sim%3D100-t%3D50.png)[~[小世界網絡-pic]~](https://github.com/yuhsiangfu/network-spreading/blob/master/image/sw_n%3D1000_k%3D5_p%3D0.1%2C%20spreading-r0%3D1.5-topk%3D1-sim%3D100-t%3D50.png) * [網絡節點分群使用基因演算法~[github]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm) * [Locus-based基因演算法(LGA)~[code]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/locus_genetic-algorithm.py) * LGA使用[disjoint-set資料結構~[code]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/util/data_structure/disjoint_set.py)[~[wiki]~](https://en.wikipedia.org/wiki/Disjoint-set_data_structure)來捕捉網絡中的[社群結構](https://en.wikipedia.org/wiki/Community_structure)，再透過基因演算法對社群結構的解做最佳化 * 網絡分群視覺化 * 產生LGA收斂曲線圖[~[karate-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/karate_gcc%2C%20lga-convergence.png)[~[dolphins-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/dolphins_gcc%2C%20lga-convergence.png)[~[LFR_benchmark_n=300_u=0.05-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/LFR_benchmark_n%3D300_u%3D0.05%2C%20lga-convergence.png)及網絡的社群結構圖[~[karate-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/karate_gcc%2C%20lga-identified-community.png)[~[dolphins-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/dolphins_gcc%2C%20lga-identified-community.png)[~[LFR_benchmark_n=300_u=0.05-pic]~](https://github.com/yuhsiangfu/locus-based-genetic-algorithm/blob/master/image/LFR_benchmark_n%3D300_u%3D0.05%2C%20lga-identified-community.png) * [網絡節點分群使用階層式合併規則~[github]~](https://github.com/yuhsiangfu/Hierarchical-Arc-Merging) * [階層式合併規則演算法~[pdf]~](https://github.com/yuhsiangfu/Hierarchical-Arc-Merging/blob/master/algorithm-1.pdf) * 使用數個節點合併規則及其建立社群結構的偵測策略，對約有250萬個節點及450萬個連結之大型網絡的節點進行分群 ### **交換學生時期 (Exchange Student Program)** 在交換學生期間，以Java程式語言為主，實作各項課程的專題程式，以下項目為參考的專題報告。 * [Advanced Image Processing and Algorithm, Final project~[github]~](https://github.com/yuhsiangfu/otsu-threshold-selection) * 實作[Otsu方法](https://en.wikipedia.org/wiki/Otsu%27s_method)於影像切割中如何選擇多個像素門檻值(multi-thresholds)的期末專題[~[專題報告-pdf]~](https://github.com/yuhsiangfu/otsu-threshold-selection/blob/master/ReadMe_project-report.pdf)[~[擷圖1-pic]~](https://github.com/yuhsiangfu/otsu-threshold-selection/blob/master/screenshot/screenshot1.jpg)[~[擷圖2-pic]~](https://github.com/yuhsiangfu/otsu-threshold-selection/blob/master/screenshot/screenshot2.jpg) * [Intelligent Information Retrieval and Text Mining, Project 3~[github]~](https://github.com/yuhsiangfu/simple-text-summarization) * 實作[字詞邊界偵測](https://en.wikipedia.org/wiki/Sentence_boundary_disambiguation)及[Porter去字尾演算法](https://tartarus.org/martin/PorterStemmer/)等方法，來實現簡易文本摘要的課程專題[~[專題報告-pdf]~](https://github.com/yuhsiangfu/simple-text-summarization/blob/master/ReadMe_project-report.pdf)[~[擷圖1-pic]~](https://github.com/yuhsiangfu/simple-text-summarization/blob/master/screenshot/screenshot2.png)[~[擷圖2-pic]~](https://github.com/yuhsiangfu/simple-text-summarization/blob/master/screenshot/screenshot3.png) * [Neural Network I: Fundamental Theory and Applications, Project 4~[github]~](https://github.com/yuhsiangfu/hopfield-neural-network) * 實作[Hopfield神經網路](https://en.wikipedia.org/wiki/Hopfield_network)來處理具有雜訊或遺失資料的數字樣式[~[專題報告-pdf]~](https://github.com/yuhsiangfu/hopfield-neural-network/blob/master/ReadMe_project-report.pdf)[~[擷圖1-pic]~](https://github.com/yuhsiangfu/hopfield-neural-network/blob/master/screenshot/screenshot1.png)[~[擷圖2-pic]~](https://github.com/yuhsiangfu/hopfield-neural-network/blob/master/screenshot/screenshot2.png) ### **碩士班時期 (Graduate Program)** 在碩士班期間，以Java程式語言，實作碩士論文的實驗程式，以下為碩士論文中對網站記錄檔(web log file)進行資料前處理的參考程式，以及工讀期間所製作與維護的網頁。 * [Data Preprocessing of Web Usage Data~[github]~](https://github.com/yuhsiangfu/data-preprocessing-of-web-usage-data) * 對網站瀏覽記錄的Log檔進行資料前處理，將使用者的[網站瀏覽記錄~[txt]~](https://github.com/yuhsiangfu/data-preprocessing-of-web-usage-data/blob/master/example/example_log-file.txt)轉換成[使用者瀏覽網站的序列~[txt]~](https://github.com/yuhsiangfu/data-preprocessing-of-web-usage-data/blob/master/example/example_browsing-sequence.txt) * [孫扶志老師的教學網頁~[website]~](https://www.cyut.edu.tw/~fcsun/)[~[擷圖-pic]~](https://drive.google.com/open?id=1CFQUQwleSil5qD2cS7buRiA58rhbi-Cl) * 使用CSS及HTML ### **大學時期 (Undergraduate Program)** 在大學時期，主要專注於網頁設計、資料庫系統及網站架設等專案，以下為工讀期間所製作與維護的網頁。 * 資訊管理系教師資料系統[~[擷圖1-pic]~](https://drive.google.com/open?id=1yLwGpp6CQ18dhO7EOvDeNquXTtJgO56R)[~[擷圖2-pic]~](https://drive.google.com/open?id=1RWPkssiedcc5aoPy9yW0yBcqEzrcmhFN)[~[擷圖3-pic]~](https://drive.google.com/open?id=1JX0M3yyDGPQo_nBY7mdTfge68n1OtKhu) * 使用ASP及HTML * 環境安全衛生中心[~[擷圖-pic]~](https://drive.google.com/open?id=1rfqPSjnjAxJAnbwMX7VBE1641y8w6xuv) * 使用ASP.NET及HTML * 臺南市東區東智里[~[擷圖1-pic]~](https://drive.google.com/open?id=1r6CtXYJUoXIawqiFw-mkaWVrz2stV9PA)[~[擷圖2-pic]~](https://drive.google.com/open?id=1NVwPPONWLulrosge9tSgV5bdIbSg2b7b)[~[文稿-pdf]~](https://drive.google.com/open?id=1mdeyawiVRObibIvxt9SyAytteK16Elnw) * 使用ASP.NET及HTML * 日昇資訊網頁樣版[~[擷圖-pic]~](https://drive.google.com/open?id=1pAepxgKWRvQz-z4QYiR8MBCH8lqXpMie) * 使用CSS及HTML ## **部落格 (Selected Blogs)** * 2011/02/25：[Self-organizing map](https://alaric-research.blogspot.tw/2011/02/self-organizing-map.html), views: [15965](https://drive.google.com/open?id=1PplZw8Vg2ppKDzWrPEvr9WKdZfWiK2mK) (2018/03/20) * 2010/02/03：[Cyclic Redundancy Check](https://alaric-research.blogspot.tw/2010/02/cyclic-redundancy-check.html), views: [9516](https://drive.google.com/open?id=13lFKEKhN_V6592efA8ihmxiitNe6OZBA) (2018/03/20) ## **線上著作(Online Book)** * Gitbook：[基礎程式設計與資料分析](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/) (2017/09，於新北市新店區) ## **論文著作(Publication)** ### **期刊論文 (Journal Papers)** #### **複雜網絡 (Complex Network)** 1. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2017). A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies. PloS one, 12(11), e0187603. (2017-IF:2.806, Rank: 23.4%[15/64])[~[website]~](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0187603)[~[pdf]~](https://drive.google.com/open?id=1rKoZzI3ZwywCBUDQhd-ALMznLG4gS8pV) 2. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2015). Using global diversity and local topology features to identify influential network spreaders. Physica A: Statistical Mechanics and its Applications, 433, 344-355. (2017-IF: 2.243, Rank: 22.7%[18/79])[~[website]~](https://www.sciencedirect.com/science/article/pii/S0378437115003040)[~[pdf]~](https://drive.google.com/open?id=16UaVbMXuZvl2PcQEKRz-5Xxo-GcDnv6c) 3. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2015). Identifying superspreader nodes in complex networks. Mathematical Problems in Engineering, 2015.[~[website]~](https://www.hindawi.com/journals/mpe/2015/675713/)[~[pdf]~](https://drive.google.com/open?id=1xO3NmlqsbCAadIdHM6sF6spzOWoEQ6Sv) #### **演化式計算 (Evolutionary Computation)** 1. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2016). Using a two-phase evolutionary framework to select multiple network spreaders based on community structure. Physica A: Statistical Mechanics and its Applications, 461, 840-853. (2017-IF: 2.243, Rank: 22.7%[18/79])[~[website]~](https://www.sciencedirect.com/science/article/pii/S0378437116303107)[~[pdf]~](https://drive.google.com/open?id=1RrL1Udq0sapYxMc-5RiTpQcmnvPa_cgz) #### **網站使用探勘 (Web Usage Mining)** 1. Lee, C. H., Lo, Y. L., & Fu, Y. H. (2011). A novel prediction model based on hierarchical characteristic of web site. Expert Systems with Applications, 38(4), 3422-3430. (2017-IF: 3.928)[~[website]~](https://www.sciencedirect.com/science/article/pii/S095741741000936X)[~[pdf]~](https://drive.google.com/open?id=1SuAZB1IZ3ZpBh84y9ANQHE2BCRf5xjud) ### **會議論文 (Conference Papers)** #### **複雜網絡 (Complex Network)** 1. Fua, Y. H., Huangb, C. Y., & Suna, C. T. (2016, March). Using network topology and rule-based strategy to identify community structure in social networks.[~[website]~](https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2016/paper/view/888)[~[pdf]~](https://drive.google.com/open?id=1Ikb0-XVvzUZyKOVxSSUZSuIN9yLmMhqY) 2. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2014, August). Using global diversity and local features to identify influential social network spreaders. In Advances in Social Networks Analysis and Mining (ASONAM), 2014 IEEE/ACM International Conference on (pp. 948-953).[~[website]~](http://ieeexplore.ieee.org/document/6921700/)[~[pdf]~](https://drive.google.com/open?id=1Bw0G_r3ILqLk9RaUloGfpWlxGPPBbrc9) 3. Huang, C. Y., Fu, Y. H., & Sun, C. T. (2014, December). Identify influential social network spreaders. In Data Mining Workshop (ICDMW), 2014 IEEE International Conference on (pp. 562-568).[~[website]~](http://ieeexplore.ieee.org/document/7022646/)[~[pdf]~](https://drive.google.com/open?id=1HpMVe6DGSuUlbiBLUt7pAnaFfx-4GUhM) #### **演化式計算 (Evolutionary Computation)** 1. Fu, Y. H., Huang, C. Y., & Sun, C. T. (2015, May). Selecting multiple network spreaders based on community structure using two-phase evolutionary framework. In Evolutionary Computation (CEC), 2015 IEEE Congress on (pp. 2482-2489).[~[website]~](http://ieeexplore.ieee.org/document/7257193/)[~[pdf]~](https://drive.google.com/open?id=1zOGhHMXqVBgz5PEZEvcTFAn9Mg3__Ot7) #### **網站使用探勘 (Web Usage Mining)** 1. Lee, C. H., & Fu, Y. H. (2008, November). Web usage mining based on clustering of browsing features. In Intelligent Systems Design and Applications, 2008. ISDA'08. Eighth International Conference on (Vol. 1, pp. 281-286).[~[website]~](http://ieeexplore.ieee.org/document/4696217/)[~[pdf]~](https://drive.google.com/open?id=1WCfmhpd16mON0Oiuoa_AeWyLt4STh5aR) 2. Lee, C. H., & Fu, Y. H. (2008, March). Two levels of prediction model for user’s browsing behavior. In Proceedings of the International MultiConference of Engineers and Computer Scientists, 2008 (Vol. 1).[~[website]~](http://www.iaeng.org/IMECS2008/doc/titles_O_Others.html)[~[pdf]~](https://drive.google.com/open?id=1RmFtHewkyDDzLZFl0i_yg1pw0mZ0huuF) 3. 李朱慧, 傅昱翔 (2008, April). 在階層式網站下具回饋機制之使用者瀏覽行為預測模型. 2008 資訊科技國際研討會 (International Conference on Advanced Information Technologies, AIT), 2008.[~[website]~](http://www.inf.cyut.edu.tw/AIT2008/)[~[pdf]~](https://drive.google.com/open?id=1zhBLm8C8H-bd9yuKac_3tUzTX187i9Uv) 4. 李朱慧, 傅昱翔 (2008, February). 結合馬可夫模型與貝氏定理之使用者瀏覽行為預測模型. 2008 International Conference on Business and Information Management, 2008.[~[pdf]~](https://drive.google.com/open?id=1kl-NY0LuW1zizhTEK-syQwOeJ-ZKSq_J) 5. 李朱慧, 傅昱翔 (2007, April). 結合關聯規則與深度優先搜尋於找尋使用者瀏覽路徑. 2007 資訊科技國際研討會 (International Conference on Advanced Information Technologies, AIT), 2007.[~[website]~](http://www.inf.cyut.edu.tw/AIT2007/)[~[pdf]~](https://drive.google.com/open?id=1MeZxNCKuB4wt50cKIZj0-X07mcitq67y) ## **教學助理經歷 (Teaching Assistant)** * 2017/09 ~ 2018/02：基礎程式設計與資料分析~(資通電軍)~[~[gitbook_線上教材]~](https://yuhsiangfu.gitbooks.io/ice101-basic-python-programming-and-data-analysis/) * 2015/02 ~ 2015/06：1032人工智慧~(交大資工)~[~[專題簡介_投影片]~](https://drive.google.com/open?id=1fMwfZ34grTC6dqEXlLq7Jn7X_mmM46n4) * 2014/09 ~ 2015/01：1031計算機科學概論~(交大x台中一中科學班)~[~[課程簡介_投影片]~](https://drive.google.com/open?id=1Dv5RXZixIIDfbtpf1OB0-ukfA3LmKv0L) * 2014/02 ~ 2014/06：1022離散數學~(交大資工)~ * 2013/02 ~ 2013/06：1012人工智慧~(交大資工)~[~[專題簡介_投影片]~](https://drive.google.com/open?id=1IK7TpGn1jaYMdhCjJUBthMQm_EL3f9Y-) * 2012/09 ~ 2013/01：1011網路應用軟體設計第2至11週~(長庚資工)~[~[課程簡介_投影片]~](https://drive.google.com/open?id=1w-q6hrqNr-_yrP3HNHy5VEC0Sv8cE7Dt) * 2012/02 ~ 2012/06：1002人工智慧~(交大資工)~[~[專題說明_投影片]~](https://drive.google.com/open?id=1D_GvjIu2NZvQU45jglV9wQbEeiJ-4BHP) * 2011/09 ~ 2012/01：1001計算機概論與程式設計~(交大資工)~[~[授課章節_大綱]~](https://drive.google.com/open?id=1pO-c5WuPT1dUN6OQ1NBATcYbKQdI_1F5) * 2011/02 ~ 2011/06：992計算機科學概論~(交大資工)~[~[專題說明_投影片]~](https://drive.google.com/open?id=1Pl2UDeBtYLHgDUodJaxCDiTiahueOhfw) ## **研究助理經歷 (Research Assistant)** 1. 計劃名稱：線上熟人社群網絡演化之交友資源加記憶的影響計劃時間：107/03 ~ 107/07 主持人：黃崇源教授執行單位：長庚大學資工系 2. 計劃名稱：最適新型流感交通阻絕策略之基因演算法優選與防疫成本效益分析計劃時間：103/10 ~ 104/07 主持人：黃崇源教授執行單位：長庚大學資工系 3. 計劃名稱：整合型計畫之子計畫一應用地理空間資料探礦與知識發掘技術於自願性地理資訊之擷取 — 以賞鳥資料為例計劃時間：101/08 ~ 102/07 主持人：黃崇源教授執行單位：長庚大學資工系計劃時間：100/03 – 101/02 4. 計劃名稱：公我意識之自我覺察代理人對於反覆囚犯困局之合作現象的影響與提升計劃時間：100/03 ~ 101/02 主持人：黃崇源教授執行單位：長庚大學資工系 5. 計劃名稱：建構「台灣通勤人口暨交通運輸網絡模型」 — 探討新型流感傳播之最佳交通阻絕策略施行方式計劃時間：99/04 ~ 100/02 主持人：黃崇源教授執行單位：長庚大學資工系 --- ###### tags: `履歷`