Search results for "Natural language"
showing 10 items of 650 documents
Visualization of tonal content with self-organizing maps and self-similarity matrices
2005
This article presents a dynamic model of tonality perception based on a short-term memory model and a self-organizing map (SOM). The model can be used for dynamic visualization of perceived tonal content, making it possible to examine the clarity and locus of tonality at any given point of time. This article also presents a method for the visualization of tonal structure using self-similarity matrices. The methods are applied to compositions of J. S. Bach, S. Barber, and J. Pachelbel. Finally, a real-time application embracing the tonality perception model is presented.
A Layered Architecture for Sentiment Classification of Products Reviews in Italian Language
2017
The paper illustrates a system for the automatic classification of the sentiment orientation expressed into reviews written in Italian language. A proper stratification of linguistic resources is adopted in order to solve the lacking of an opinion lexicon specifically suited for the Italian language. Experiments show that the proposed system can be applied to a wide range of domains.
Positionless aspect based sentiment analysis using attention mechanism.
2021
Abstract Aspect-based sentiment analysis (ABSA) aims at identifying fine-grained polarity of opinion associated with a given aspect word. Several existing articles demonstrated promising ABSA accuracy using positional embedding to show the relationship between an aspect word and its context. In most cases, the positional embedding depends on the distance between the aspect word and the remaining words in the context, known as the position index sequence. However, these techniques usually employ both complex preprocessing approaches with additional trainable positional embedding and complex architectures to obtain the state-of-the-art performance. In this paper, we simplify preprocessing by …
A Geometric Algebra Based Distributional Model to Encode Sentences Semantics
2013
Word space models are used to encode the semantics of natural language elements by means of high dimensional vectors [23]. Latent Semantic Analysis (LSA) methodology [15] is well known and widely used for its generalization properties. Despite of its good performance in several applications, the model induced by LSA ignores dynamic changes in sentences meaning that depend on the order of the words, because it is based on a bag of words analysis. In this chapter we present a technique that exploits LSA-based semantic spaces and geometric algebra in order to obtain a sub-symbolic encoding of sentences taking into account the words sequence in the sentence. © 2014 Springer-Verlag Berlin Heidel…
Words and Patterns
2002
In this paper some new ideas, problems and results on patterns are proposed. In particular, motivated by questions concerning avoidability, we first study the set of binary patterns that can occur in one infinite binary word, comparing it with the set of factors of the word. This suggests a classification of infinite words in terms of the "difference" between the set of its patterns and the set of its factors. The fact that each factor in an infinite word can give rise to several distinct patterns leads to study the set of patterns of a single finite word. This set, endowed with a natural order relation, defines a poset: we investigate the relationships between the structure of such a poset…
Features for Text Comparison
2008
The main purpose of this paper is to deliver appropriate tool to find similarities between texts. The area of interest covers comparing large amount of different texts grouped in various areas of knowledge. Similarity is defined as distance between two texts and as this the measure may be calculated as the set of parameters based on features.
INTEGRATING ONTOLOGY AND COGNITIVE LINGUISTICS FOR NATURAL LANGUAGE PRODUCTION AND UNDERSTANDING A CASE OF STUDY IN FLUID CONSTRUCTION GRAMMAR.
2012
A multi‐agent system for itinerary suggestion in smart environments
2021
Abstract Modern smart environments pose several challenges, among which the design of intelligent algorithms aimed to assist the users. When a variety of points of interest are available, for instance, trajectory recommendations are needed to suggest users the most suitable itineraries based on their interests and contextual constraints. Unfortunately, in many cases, these interests must be explicitly requested and their lack causes the so‐called cold‐start problem. Moreover, lengthy travelling distances and excessive crowdedness of specific points of interest make itinerary planning more difficult. To address these aspects, a multi‐agent itinerary suggestion system that aims at assisting t…
QuASIt: A Cognitive Inspired Approach to Question Answering for the Italian Language
2016
In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt …
An Emotional Talking Head for a Humoristic Chatbot
2011
The interest about enhancing the interface usability of applications and entertainment platforms has increased in last years. The research in human-computer interaction on conversational agents, named also chatbots, and natural language dialogue systems equipped with audio-video interfaces has grown as well. One of the most pursued goals is to enhance the realness of interaction of such systems. For this reason they are provided with catchy interfaces using humanlike avatars capable to adapt their behavior according to the conversation content. This kind of agents can vocally interact with users by using Automatic Speech Recognition (ASR) and Text To Speech (TTS) systems; besides they can c…