Using Opinion Scores of Words for Sentence-Level Opinion Extraction

نویسندگان

  • Lun-Wei Ku
  • Yong-Sheng Lo
  • Hsin-Hsi Chen
چکیده

The opinion analysis task is a pilot study task in NTCIR-6. It contains the challenges of opinion sentence extraction, opinion polarity judgment, opinion holder extraction and relevance sentence extraction. The three former are new tasks, and the latter is proven to be tough in TREC. In this paper, we introduce our system for analyzing opinionated information. Several formulae are proposed to decide the opinion polarities and strengths of words from composed characters and then further to process opinion sentences. The negation operators are also taken into consideration in opinion polarity judgment, and the opinion operators are used as clues to find the locations of opinion holders. The performance of the opinion extraction and polarity judgment achieves the f-measure 0.383 under the lenient metric and 0.180 under the strict metric, which is the second best of all participants.

برای دانلود رایگان 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

Using Polarity Scores of Words for Sentence-level Opinion Extraction

The opinion analysis task is a pilot study task in NTCIR-6. It contains the challenges of opinion sentence extraction, opinion polarity judgment, opinion holder extraction and relevance sentence extraction. The three former are new tasks, and the latter is proven to be tough in TREC. In this paper, we introduce our system for analyzing opinionated information. Several formulae are proposed to d...

متن کامل

Feature extraction in opinion mining through Persian reviews

Opinion mining deals with an analysis of user reviews for extracting their opinions, sentiments and demands in a specific area, which can play an important role in making major decisions in such area. In general, opinion mining extracts user reviews at three levels of document, sentence and feature. Opinion mining at the feature level is taken into consideration more than the other two levels d...

متن کامل

Using Morphological and Syntactic Structures for Chinese Opinion Analysis

This paper employs morphological structures and relations between sentence segments for opinion analysis on words and sentences. Chinese words are classified into eight morphological types by two proposed classifiers, CRF classifier and SVM classifier. Experiments show that the injection of morphological information improves the performance of the word polarity detection. To utilize syntactic s...

متن کامل

Sentence-Level Opinion Analysis by CopeOpi in NTCIR-7

In this paper, we introduce our system, CopeOpi, for analyzing opinionated information in NTCIR-7 MOAT task’s document collections. We participated in all tasks except opinion target extraction and submitted three runs for both simplified and traditional Chinese sides. For opinion extraction task, our algorithm was based on the bag-ofcharacter methods proposed in NTCIR-6 and considered morpholo...

متن کامل

Opinion Sentence and Topic Relevant Sentence Extraction by Using Coherent Structure among the Sentences

We developed a new sentence extraction framework, the Sliding Window Framework, by using coherent structure among the sentences. Coherent structure means that the sentences that relate to a certain topic in an article are written in clusters to preserve the logical organization. To use the structure, our method makes blocks that consist of sentences in a window of a certain size, then estimates...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007