TAILIEUCHUNG - Báo cáo khoa học: "Dictionary Definitions based Homograph Identification using a Generative Hierarchical Model"

A solution to the problem of homograph (words with multiple distinct meanings) identification is proposed and evaluated in this paper. It is demonstrated that a mixture model based framework is better suited for this task than the standard classification algorithms – relative improvement of 7% in F1 measure and 14% in Cohen’s kappa score is observed. | Dictionary Definitions based Homograph Identification using a Generative Hierarchical Model Anagha Kulkarni Jamie Callan Language Technologies Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave Pittsburgh Pa 15213 USA anaghak callan @ Abstract A solution to the problem of homograph words with multiple distinct meanings identification is proposed and evaluated in this paper. It is demonstrated that a mixture model based framework is better suited for this task than the standard classification algorithms -relative improvement of 7 in F1 measure and 14 in Cohen s kappa score is observed. 1 Introduction Lexical ambiguity resolution is an important research problem for the fields of information retrieval and machine translation Sanderson 2000 Chan et al. 2007 . However making fine-grained sense distinctions for words with multiple closely-related meanings is a subjective task Jorgenson 1990 Palmer et al. 2005 which makes it difficult and error-prone. Fine-grained sense distinctions aren t necessary for many tasks thus a possibly-simpler alternative is lexical disambiguation at the level of homographs Ide and Wilks 2006 . Homographs are a special case of semantically ambiguous words Words that can convey multiple distinct meanings. For example the word bark can imply two very different concepts - outer layer of a tree trunk or the sound made by a dog and thus is a homograph. Ironically the definition of the word homograph is itself ambiguous and much debated however in this paper we consistently use the above definition. If the goal is to do word-sense disambiguation of homographs in a very large corpus a manually-generated homograph inventory may be impractical. In this case the first step is to determine which words in a lexicon are homographs. This problem is the subject of this paper. 2 Finding the Homographs in a Lexicon Our goal is to identify the homographs in a large lexicon. We assume that manual labor is a scarce resource

• Báo cáo khoa học
• Dictionary Definitions
• Homograph Identification
• Generative Hierarchical Model
• báo cáo khoa học
• báo cáo ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Statistical Sense Disambiguation
• Relatively Small Corpora
• mô hình ngôn ngữ
• SEMANTICALLY SIGNIFICANT PATTERNS
• Judith Markowitz
• scientific reports
• model language
• process natural language
• PARSING AND TEXT PROCESSING
• THE ANALYSIS OF DICTIONARY DEFINITIONS
• Thomas Ahlswede
• precise definitions
• comprehensive update
• mathematics dictionary
• the best selling
• accurate
• clear precise definitions
• electrical engineering dictionary
• kỹ thuật điện tử
• từ điển điện tử
• anh văn chuyên ngành
• tài liệu điện tử
• finance
• definitions and explanations
• including step by step
• Exhibits and statistical data
• as needed
• Encyclopedic Dictionary
• important directives
• electrical
• electronic and electrical industry
• electrical engineering
• electrical professional
• specialized dictionaries li arts
• electronic dictionary
• Ed
• Phillip A
• Laplante
• specialized dictionaries electricity
• Definitions
• TOEIC Test
• Answering Correctly
• Progressive Practice
• Reading Test