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.
In this paper, we propose a method of automatically extracting word hierarchies based on the inclusion relation of appearance patterns from corpora. We apply a complementary similarity measure to find a hierarchical word structure. This similarity measure was developed for the recognition of degraded machineprinted text in the field and can be applied to estimate one-to-many relations. Our purpose is to extract word hierarchies from corpora automatically.
Previous work has shown that automatic methods can be used in building semantic lexicons. This work goes a step further by automatically creating not just clusters of related words, but a hierarchy of nouns and their hypernyms, akin to the hand-built hierarchy in WordNet.
This paper shows how DATR, a widely used formal language for lexical knowledge representation, can be used to define an I_TAG lexicon as an inheritance hierarchy with internal lexical rules. A bottom-up featural encoding is used for LTAG trees and this allows lexical rules to be implemented as covariation constraints within feature structures. Such an approach eliminates the considerable redundancy otherwise associated with an LTAG lexicon.
Many researchers have attempted to predict the Enron corporate hierarchy from the data. This work, however, has been hampered by a lack of data. We present a new, large, and freely available gold-standard hierarchy. Using our new gold standard, we show that a simple lower bound for social network-based systems outperforms an upper bound on the approach taken by current NLP systems.
In recent years, statistical approaches on ATR (Automatic Term Recognition) have achieved good results. However, there are scopes to improve the performance in extracting terms still further. For example, domain dictionaries can improve the performance in ATR. This paper focuses on a method for extracting terms using a dictionary hierarchy. Our method produces relatively good results for this task.
This paper proposes a description of German word order including phenomena considered as complex, such as scrambling, (partial) VP fronting and verbal pied piping. Our description relates a syntactic dependency structure directly to a topological hierarchy without resorting to movement or similar mechanisms.
In many types of technical texts, meaning is embedded in noun compounds. A language understanding program needs to be able to interpret these in order to ascertain sentence meaning. We explore the possibility of using an existing lexical hierarchy for the purpose of placing words from a noun compound into categories, and then using this category membership to determine the relation that holds between the nouns. In this paper we present the results of an analysis of this method on twoword noun compounds from the biomedical domain, obtaining classiﬁcation accuracy of approximately 90%. ...
A set of labeled classes of instances is extracted from text and linked into an existing conceptual hierarchy. Besides a significant increase in the coverage of the class labels assigned to individual instances, the resulting resource of labeled classes is more effective than similar data derived from the manually-created Wikipedia, in the task of attribute extraction over conceptual hierarchies.
Khoá luận tốt nghiệp Hệ thống thông tin địa lý: Tích hợp bài toán AHP (Analytic Hierarchy Process) chuẩn hoá Vector vào phần mềm ArcGis được thực hiện nhằm xây dựng thành công công cụ tính bài toán AHP chuẩn hoá vector trên phần mềm ArcGis nhằm tránh sai số cộng dồn thực hiện qua nhiều bước, và tiết kiệm được thời gian tính toán tránh được sai số khi tính bằng tay.
Formal Languages & Automata: Chapter 10 - A Hierarchy of Formal Languages and Automata presents about Recursively Enumerable Languages, Recursive Languages, Unrestricted Grammars, Context-Sensitive Grammars, Linear Bounded Automata.
Learn from the pros! Illustrated throughout with full-color images of top sites -- including those of Starbucks, Purina, the Getty Center, Salon Magazine, and Carnegie Hall -- this hands-on guide is your blueprint for successful Web architecture. Each chapter explores a different secret, from building a hierarchy and mapping links to developing vivid themes and planning for expansion.
Principle of Locality:
Programs access a small proportion of their address space at any time.
Items accessed recently are likely to be accessed again soon,
e.g., instructions in a loop, induction variables.
Items near those accessed recently are likely to be accessed soon,
E.g., sequential instruction access, array data.
In this chapter, the following content will be discussed: Distinctive properties of living systems, biomolecules: molecules of life, biomolecular hierarchy, properties of biomolecules, organization and structure of cells, viruses as cell parasites.
Tham khảo tài liệu 'an introduction to intelligent and autonomous control-chapter 4:design of structure-based hierarchies for distributed intelligent control', công nghệ thông tin, quản trị web phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả
Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Hydrothermal synthesis of MnO2/CNT nanocomposite with a CNT core/porous MnO2 sheath hierarchy architecture for supercapacitors
Mở rộng một cấp bậc Inheritance Trong tập thể dục sau đây, bạn sẽ tự làm quen với một hệ thống cấp bậc nhỏ của giao diện và các lớp học đó cùng nhau thực hiện một khuôn khổ rất đơn giản. khuôn khổ là một Microsoft Windows ứng dụng mô phỏng đọc một C # nguồn tập tin và phân loại nội dung của nó vào thẻ
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: The hierarchy of stability and predictability in orthognathic surgery with rigid fixation: an update and extension