A Preliminary Evaluation of the Impact of Syntactic Structure in Semantic Textual Similarity and Semantic Relatedness Tasks

نویسندگان

  • Ngoc Phuoc An Vo
  • Octavian Popescu
چکیده

The well related tasks of evaluating the Semantic Textual Similarity and Semantic Relatedness have been under a special attention in NLP community. Many different approaches have been proposed, implemented and evaluated at different levels, such as lexical similarity, word/string/POS tags overlapping, semantic modeling (LSA, LDA), etc. However, at the level of syntactic structure, it is not clear how significant it contributes to the overall accuracy. In this paper, we make a preliminary evaluation of the impact of the syntactic structure in the tasks by running and analyzing the results from several experiments regarding to how syntactic structure contributes to solving these tasks.

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

Evaluation of “Mosaic 1 Reading”: A Microstructural Approach to Textual Analysis of Pedagogical Materials

To analyze and evaluate textbooks, researchers have either proposed scales and checklists to be filled by teachers and learners or conducted qualitative investigations of the match between SLA theories and textbook activities. This study, however, employs the microstructural approach of schema theory to scrutinize the reading passages of “Mosaic 1 Reading”. To this end, 17 passages of the textb...

متن کامل

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

متن کامل

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

متن کامل

برچسب‌زنی خودکار نقش‌های معنایی در جملات فارسی به کمک درخت‌های وابستگی

Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...

متن کامل

Developing a Semantic Similarity Judgment Test for Persian Action Verbs and Non-action Nouns in Patients With Brain Injury and Determining its Content Validity

Objective: Brain trauma evidences suggest that the two grammatical categories of noun and verb are processed in different regions of the brain due to differences in the complexity of grammatical and semantic information processing. Studies have shown that the verbs belonging to different semantic categories lead to neural activity in different areas of the brain, and action verb processing is r...

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 2015