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義大利文翻譯語言翻譯公司Freescan 是一款沒有袖帶的血壓計，可以或許直接透過脈搏讀取手藝來丈量血壓，最重要的是 Freescan 的體積相當小、丈量速度快，可以放進口袋中，豈論是在家中、餐廳、旅遊都能隨時隨地的把握血壓數據翻譯

德語翻譯中文語言翻譯公司
提醒您，不是每一個人都能捐血！

中翻柬埔寨語言翻譯公司課程名稱︰天然語言處理 課程性質︰系內選修 課程教師︰陳信希 開課學院：電資學院 開課系所︰資訊工程學系 考試日期（年代日）︰2016/04/21 測驗時限（分鐘）：180 mins 試題 : 01. Machine translation (MT) is one of practical NLP applications. The development of MT systems has a long history翻譯社 but still has space to improve. Please address two linguistic phenomena to explain why MT systems are challenging. (10pts) 02. An NLP system can be implemented in a pipeline, including modules of morphological processing, syntactic analysis翻譯社 semantic interpretation and context analysis. Please use the following news story to describe the concepts behind. You are asked to mention one task in each module. (10pts) 這場地震可能影響日相安倍晉三的施政計畫翻譯安倍十八日說，消費睡調漲的 計畫不會改變。 03. Ambiguity is inherent in natural language. Please describe why ambiguity may happen in each of the following cases. (10pts) (a) Prepositional phrase attachment. (b) Noun-noun compound. (c) Word: bass 04. Why the extraction of multiword expressions is critical for NLP applications? Please propose a method to check if an extracted multiword expression meets the non-compositionality criterion, (10pts) 05. Mutual information and likelihood ratio are commonly used to find collocations in a corpus. Please describe the ideas of these two methods. (10pts) 06. Emoticons are commonly used in social media. They can be regarded as a special vocabulary in a language. Emoticon understanding is helpful to understand the utterances in an interaction. Please propose an "emoticon" embedding approach to represent each emoticons as a vector, and find the most 5 relevant words to each emoticon. (10pts) 07. To deal with unseen n-grams翻譯社 smoothing techniques are adopted in conventional language modeling approach. They are applied to n-grams to reallocate probability mass from observed n-grams to unobserved n-grams, producing better estimates for unseen data. Please show a smoothing technique for the conventional language model翻譯社 and discuss why neural network language model (NNLM) can achieve better generalization for unseen n-grams. (10pts) 08. In HMM learning, we aim at inferring the best model parameters, given a skeletal model and an observation sequence. The following two equations are related to compute the state transition probabilities. Σ_{t=1}^{T-1} ξ_t(i, j) \hat{a}_{ij} = --------------------------------------- Σ_{t=1}^{T-1} Σ_{j=1}^{N} ξ_t(i翻譯社j) α_t(i) a_{ij} b_j(o_{t+1}) β_{t+1}(j) ξ_t(i, j) = ----------------------------------------- α_T(q_F) Please answer the following questions. (10pts) (a) Intuitively, we can generate all possible paths for the given observation sequence, and compute total times of a transition which the observation passes. Which part in the above equations avoids the generation of all possible paths? (b) Which part in the above equations is related to prorate count to estimate the transition probability of a transition? 09. Many NLP problems can be cast as a sequence labelling problem. Part of speech tagging is a typical example. Given a model and an observation sequence, we aim at finding the most probable state sequence. Please explain why this process is called a decoding process. In addition翻譯社 please give another application which can be also treated as a sequence labelling problem. (10pts) 10. What is long-distance dependencies or unbounded dependencies? Why such kinds of linguistic phenomena are challenging in NLP? (10pts) 11. Part of speech tagging can be formulated in the following two alternatives: Model 1: \hat{t}_1^n = argmax_{t_1^n} Π_{i=1}^n P(w_i|t_i) P(t_i|t_{i-1}) Model 2: \hat{t}_1^n = argnax_{t_1^n} Π_{i=1}^n P(t_i|w_i, t_{i-1}) Please answer the following questions. (10pts) (a) Which one is discriminative model? (b) Which one can introduce more features? (c) Which one can use Viterbi algorithm to improve the speed? (d) Which one is derived on the basis of Bayes rule? 12. The following parsing tree is selected from Chinese Treebank 8.0. What NP and VP rules can be extracted from this parsing tree to form parts of a treebank grammer? (10pts) ( (IP (IP (NP-SBJ (NN 建築)) | (VP (VC 是) | | (NP-PRD (CP-APP (IP (NP-SBJ (-NONE- *pro*)) | | | | (VP (VV 開發) | | | | | (NP-PN-OBJ (NR 浦東)))) | | | | (DEC 的)) | | | (QP (CD 一) | | | (CLP (M 項))) | | | (ADJP (JJ 首要)) | | | (NP (NN 經濟) | | | (NN 運動))))) | (PU 。) | (IP (NP-SBJ (-NONE- *pro*)) | (VP (DP-TMP (DT 這些) | | | (CLP (M 年))) | | (VP (VE 有) | | (IP-OBJ (NP-SBJ (NP (QP (CD 數百) | | | | | (CLP (M 家))) | | | | | (NP (NN 建築) | | | | | (NN 公司))) | | | | (PU 、) | | | | (NP (QP (CD 四千餘) | | | | | (CLP (M 個))) | | | | | (NP (NN 建築) | | | | | (NN 工地)))) | | | (VP (VV 遍布) | | | | (PP-LOC (P 在) | | | | | (LCP (NP (DP (DT 這) | | | | | | (CLP (M 片))) | | | | | | (NP (NN 熱土))) | | | | | (LC 上)))))))) | (PU 。)) )

羅馬尼亞語翻譯語言翻譯公司

韓文翻譯語言翻譯公司

法律翻譯服務語言翻譯公司

Q：那又是什麼使你的研究方式如斯與眾分歧？

歐斯干語翻譯語言翻譯公司

耐諾斯克挪威文翻譯語言翻譯公司

只是拍下所有人毫無諱飾的模樣
Just picture everybody naked

古英文翻譯語言翻譯公司陳建志劉景寬 石友翻臉
董事會箝制校長 兩邊破裂

班達語翻譯語言翻譯公司

https://www.facebook.com/pages/Ginas-Corner-%E5%90%89%E5%A8%9C%E8%A7%92/194320970743685

塞爾庫普文翻譯語言翻譯公司

台北市松山慈惠堂昨晚於小巨蛋一場音樂晚會中，公然捐贈5000個室第用火災警報器給新北市政府，火災警報器未來將由新北市消防局優先免費安裝於獨居老人及高風險家庭等弱勢民眾住家，藉此下降火災成災機率翻譯新北市消防局指出，新北市需安裝室第用火警警報器家數高達63萬5千多戶，高居全國之冠，其中茕居老人、高風險家庭、巷弄狹窄地域等火警潛勢因子較高地區，自2007年起，新北市消防局即鼎力協助補助安裝，同時取得市長支持推動民間資本共同介入，截至今朝積累安裝約6萬2千戶，高齡生齒(65歲以上)火災滅亡人數下落比率高達百分之55。因預算和獲贈數目有限，獲贈的火警警報器將優先免費安裝於茕居白叟及高風險家庭等弱勢民眾住家，新北市消防局同時呼籲，為了保障生命和財產安全，民眾可至消防器材公司、網路商鋪及居家修繕賣場等處，自行選購安裝住宅用火警警報器，平時多一分專心，將大幅削減災難産生的機會。（突發中間陳韋劭／新北報道）