A Hybrid Method of Linguistic Features and Clustering Approach for Identifying Biomedical Named Entities
نویسندگان
چکیده
منابع مشابه
A hybrid method for extracting relations between Arabic named entities
Relation extraction is a very useful task for several natural language processing applications, such as automatic summarization and question answering. In this paper, we present our hybrid approach to extracting relations between Arabic named entities. Given that Arabic is a rich morphological language, we build a linguistic and learning model to predict the positions of the words that express ...
متن کاملeplicitation in interlingual and intralingual translations of shahnameh ferdowsi: a text linguistic approach
بررسی و مقایسه تفاوتها و شباهت های ترجمه ی درون زبانی و برون زبانی با تمرکز بر زبانشناسی متن. برای امر مقایسه میزان بسامد تصریح به کار رفته در ترجمه ی درون زبانی و نیز برون زبانی شاهنامه ی فردوسی مورد بررسی قرار گرفت.
Metonimy resolution for named entities: an hybrid approach
Named Entity metonymy resolution is a challenging natural langage processing task, which has been recently subject to a growing interest. In this paper, we describe the method we have developed in order to solve Named entity metonymy in the framework of the SemEval 2007 competition. In order to perform Named Entity metonymy resolution on location names and company names, as required for this ta...
متن کاملIntegrating linguistic knowledge into a conditional random fieldframework to identify biomedical named entities
As new high-throughput technologies have created an explosion of biomedical literature, there arises a pressing need for automatic information extraction from the literature bank. To this end, biomedical named entity recognition (NER) from natural language text is indispensable. Current NER approaches include: dictionary based, rule based, or machine learning based. Since there is no consolidat...
متن کاملRecognising Nested Named Entities in Biomedical Text
Although recent named entity (NE) annotation efforts involve the markup of nested entities, there has been limited focus on recognising such nested structures. This paper introduces and compares three techniques for modelling and recognising nested entities by means of a conventional sequence tagger. The methods are tested and evaluated on two biomedical data sets that contain entity nesting. A...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Asian Journal of Applied Sciences
سال: 2015
ISSN: 1996-3343
DOI: 10.3923/ajaps.2015.210.216