ASAP: Automatic Semantic Alignment for Phrases
نویسندگان
چکیده
In this paper we describe the ASAP system (Automatic Semantic Alignment for Phrases)1 which participated on the Task 1 at the SemEval-2014 contest (Marelli et al., 2014a). Our assumption is that STS (Semantic Text Similarity) follows a function considering lexical, syntactic, semantic and distributional features. We demonstrate the learning process of this function without any deep preprocessing achieving an acceptable correlation.
منابع مشابه
ASAP-II: From the Alignment of Phrases to Textual Similarity
ThisThis work is licensed under a Creative Commons Attribution 4.0 International Licence. Page numbers and proceedings footer are added by the organisers. Licence details: http://creativecommons.org/licenses/by/4.0/ paper describes the second version of the ASAP system1 and its participation in the SemEval-2015, task 2a on Semantic Textual Similarity (STS). Our approach is based on computing th...
متن کاملSemantics-based Automatic Literal Reconstruction Of Dictations
This paper describes a method for the automatic literal reconstruction of dictations in the domain of medical reports. The raw output of an automatic speech recognition system and the final report edited by a professional medical transcriptionist serve as input to the reconstruction algorithm. Reconstruction is based on automatic alignment between the speech recognition result and the edited re...
متن کاملAutomatic Extraction of Medical Term Variants from Mutilingual Parallel Translations
The extraction of terms and their variants is an important issue in various applications of natural language processing (NLP), such as question answering and information retrieval. In this chapter we discuss a method to automatically extract medical terms and their variants from a multilingual corpus of parallel translations. As a first step terms are extracted using a pattern-based approach. I...
متن کاملConstructing lexicons of relational phrases
Knowledge Bases are one of the key components of Natural Language Understanding systems. For example, DBpedia, YAGO, and Wikidata capture and organize knowledge about named entities and relations between them, which is often crucial for tasks like Question Answering and Named Entity Disambiguation. While Knowledge Bases have good coverage of prominent entities, they are often limited with respe...
متن کاملCombining Web-Based Searching with Latent Semantic Analysis to Discover Similarity Between Phrases
Determining semantic similarity between words, concepts and phrases is important in many areas within Artificial Intelligence. This includes the general areas of information retrieval, data mining, and natural language processing. Existing approaches have primarily focused on noun to noun synonym comparison. We propose a new technique for the comparison of general expressions that combines web ...
متن کاملذخیره 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 2014