Exploiting the performance of dictionary-based bio-entity name recognition in biomedical literature

نویسندگان

  • Zhihao Yang
  • Hongfei Lin
  • Yanpeng Li
چکیده

Bio-entity name recognition is the key step for information extraction from biomedical literature. This paper presents a dictionary-based bio-entity name recognition approach. The approach expands the bio-entity name dictionary via the Abbreviation Definitions identifying algorithm, improves the recall rate through the improved edit distance algorithm and adopts some post-processing methods including Pre-keyword and Post-keyword expansion, Part of Speech expansion, merge of adjacent bio-entity names and the exploitation of the contextual cues to further improve the performance. Experiment results show that with this approach even an internal dictionary-based system could achieve a fairly good performance.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Developing a hybrid dictionary-based bio-entity recognition technique

BACKGROUND Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. METHODS This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources a...

متن کامل

A Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features

Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...

متن کامل

Incorporating domain knowledge in chemical and biomedical named entity recognition with word representations

BACKGROUND Chemical and biomedical Named Entity Recognition (NER) is an essential prerequisite task before effective text mining can begin for biochemical-text data. Exploiting unlabeled text data to leverage system performance has been an active and challenging research topic in text mining due to the recent growth in the amount of biomedical literature. We present a semi-supervised learning m...

متن کامل

Gene/Protein/Family Name Recognition In Biomedical Literature

Rapid advances in the biomedical field have resulted in the accumulation of numerous experimental results, mainly in text form. To extract knowledge from biomedical papers, or use the information they contain to interpret experimental results, requires improved techniques for retrieving information from the biomedical literature. In many cases, since the information is required in gene units, r...

متن کامل

بهبود شناسایی موجودیت‌های نامدار فارسی با استفاده از کسره اضافه

Named entity recognition is a process in which the people’s names, name of places (cities, countries, seas, etc.) and organizations (public and private companies, international institutions, etc.), date, currency and percentages in a text are identified. Named entity recognition plays an important role in many NLP tasks such as semantic role labeling, question answering, summarization, machine ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Computational biology and chemistry

دوره 32 4  شماره 

صفحات  -

تاریخ انتشار 2008