This paper explores techniques to take advantage of the fundamental difference in structure between hidden Markov models (HMM) and hierarchical hidden Markov models (HHMM). The HHMM structure allows repeated parts of the model to be merged together. A merged model takes advantage of the recurring patterns within the hierarchy, and the clusters that exist in some sequences of observations, in order to increase the extraction accuracy.
Teach children to learn English is quite hard work and complex by young are not really conscious of learning as adults and most are very giddy. For children focused on lessons, teachers need teaching combined with the story of the visual image, you are invited to consult the text book "Hidden in the forest" below for additional documents for demand for learning and research.
The automatic coding of clinical documents is an important task for today’s healthcare providers. Though it can be viewed as multi-label document classiﬁcation, the coding problem has the interesting property that most code assignments can be supported by a single phrase found in the input document. We propose a Lexically-Triggered Hidden Markov Model (LT-HMM) that leverages these phrases to improve coding accuracy.
This paper describes an unsupervised dynamic graphical model for morphological segmentation and bilingual morpheme alignment for statistical machine translation. The model extends Hidden Semi-Markov chain models by using factored output nodes and special structures for its conditional probability distributions. It relies on morpho-syntactic and lexical source-side information (part-of-speech, morphological segmentation) while learning a morpheme segmentation over the target language. Our model outperforms a competitive word alignment system in alignment quality. ...
This paper presents a supervised pronoun anaphora resolution system based on factorial hidden Markov models (FHMMs). The basic idea is that the hidden states of FHMMs are an explicit short-term memory with an antecedent buffer containing recently described referents. Thus an observed pronoun can ﬁnd its antecedent from the hidden buffer, or in terms of a generative model, the entries in the hidden buffer generate the corresponding pronouns.
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, an HMM is used to model text at the document level. This modelling might cause undesired redundancy in extraction in the sense that more than one ﬁller is identiﬁed and extracted. We propose to use HMMs to model text at the segment level, in which the extraction process consists of two steps: a segment retrieval step followed by an extraction step. ...
We would like to draw attention to Hidden Markov Tree Models (HMTM), which are to our knowledge still unexploited in the ﬁeld of Computational Linguistics, in spite of highly successful Hidden Markov (Chain) Models. In dependency trees, the independence assumptions made by HMTM correspond to the intuition of linguistic dependency. Therefore we suggest to use HMTM and tree-modiﬁed Viterbi algorithm for tasks interpretable as labeling nodes of dependency trees.
This paper presents an unsupervised topic identiﬁcation method integrating linguistic and visual information based on Hidden Markov Models (HMMs). We employ HMMs for topic identiﬁcation, wherein a state corresponds to a topic and various features including linguistic, visual and audio information are observed. Our experiments on two kinds of cooking TV programs show the effectiveness of our proposed method.
This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is especially advantageous for part-of-speech tagging because the resulting transducer can be composed with other transducers that encode correction rules for the most frequent tagging errors. The speed of tagging is also improved. The described methods have been implemented and successfully tested on six languages.
This paper investigates transforms of split dependency grammars into unlexicalised context-free grammars annotated with hidden symbols. Our best unlexicalised grammar achieves an accuracy of 88% on the Penn Treebank data set, that represents a 50% reduction in error over previously published results on unlexicalised dependency parsing.
This hybrid system participated in the 1993 ATIS natural language evaluation. Although only four months old, the scores achieved by the combined system were quite respectable. Because of differences between language understanding and speech recognition, significant changes are required in the hidden Markov model methodology. Unlike speech, where each phoneme results in a local sequence of spectra, the relation between the meaning of a sentence and the sequence of words is not a simple linear sequential model. ...
During the last thirty years of his life, Albert Einstein sought relentlessly for a so-called unified field theory—a theory capable of
describing nature's forces within a single, all-encompassing, coherent framework. Einstein was not motivated by the things we
often associate with scientific undertakings, such as trying to explain this or that piece of experimental data. Instead, he was driven
by a passionate belief that the deepest understanding of the universe would reveal its truest wonder: the simplicity and power of the
principles on which it is based.
This collection will help people at all levels understand the fundamental theories and practices of effective decision making so that they can make better decisions in their personal and professional lives. Articles include: The Effective Decision by Peter F. Drucker; Even Swaps: A Rational Method for Making Trade-offs by John S. Hammond, Ralph L.
Có một số file dữ liệu, thông tin, phim, ảnh... của cá nhân mà các bạn không muốn cho
người khác xem khi họ xài chung máy tính nên các bạn nghĩ ra cách sử dụng chế độ
Hidden ẩn nó đi. Nhưng khi cần vào giao diện cũ, muốn mở lại nhưng nó đã biến mất
không mở được.
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Mines gems like unlocking hidden settings, customizing boot screens, supercharging online and program launch speed, maximizing the file system and RAM, and dumping hated features for good
Written by the creator of TweakXP.com, a site considered Mecca for Windows hackers and trusted by more than ten million Windows XP users worldwide...