Search results for "Natural Language Processing"
showing 10 items of 413 documents
Sub-Symbolic Semantic Layer in Cyc for Intuitive Chat-Bots
2007
The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data-driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "subsymbolic semantic layer" automatically a…
Sub-Symbolic Knowledge Representation for Evocative Chat-Bots
2008
A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE a…
A combined semantic-syntactic sentence analysis for students assessment
2010
TutorJ is an Intelligent Tutoring System able to fulfill the requests of a student with a learning path inside didactical materials. To this aim, it must assess the level of training of the learner. In the first version of TutorJ this goal was reached through a conversational agent whose linguistic interaction enriched by a LSA-based text analysis. This approach suffers from the limitations of LSA as a bag-of- words approach. Next, morphosyntactic comparison of sentences' structures was implemented. In this paper we present a new version of the assessment procedure involving both semantic, and morphosyntactic analysis user's sentences.
Sentence Induced Transformations in Conceptual Spaces
2008
The proposed work illustrates how "primitive concepts" can be automatically induced from a text corpus. The primitive concepts are identified by the orthonormal axis of a "conceptual" space induced by a methodology inspired to the latent semantic analysis approach. The methodology represents a natural language sentence by means of a set of rotations of an orthonormal basis in the "conceptual"space. The rotations, triggered by the sequence of words composing the sentence and realized by means of geometric algebra rotors, allow to highlight "conceptual" relations that can arise among the primitive concepts.
A Novel Approach for Supporting Italian Satire Detection Through Deep Learning
2021
Satire is a way of criticizing people (or ideas) by ridiculing them on political, social, and morals topics often used to denounce political and societal problems, leveraging comedic devices such as parody exaggeration, incongruity, etc.etera. Detecting satire is one of the most challenging computational linguistics tasks, natural language processing, and social multimedia sentiment analysis. In particular, as satirical texts include figurative communication for expressing ideas/opinions concerning people, sentiment analysis systems may be negatively affected; therefore, satire should be adequately addressed to avoid such systems’ performance degradation. This paper tackles automatic satire…
A Study on Classification Methods Applied to Sentiment Analysis
2013
Sentiment analysis is a new area of research in data mining that concerns the detection of opinions and/or sentiments in texts. This work focuses on the application and the comparison of three classification techniques over a text corpus composed of reviews of commercial products in order to detect opinions about them. The chosen domain is about "perfumes", and user opinions composing the corpus are written in Italian language. The proposed approach is completely data-driven: a Term Frequency / Inverse Document Frequency (TFIDF) terms selection procedure has been applied in order to make computation more efficient, to improve the classification results and to manage some issues related to t…
A User-Friendly Interface for Fingerprint Recognition Systems Based on Natural Language Processing
2009
Biometric recognition systems represent a valid solution to the safety problem of internet accessibility, even if they do not always provide an environment easily comprehensible by users and operators with a mid-level of competence. This gap can be partially filled if, instead of using the conventional access routines to the authentication system, the user could simply write to the system through the interface and using high level sentences and requests be able to use its own natural language to reach the intended goal. On the other hand, biometrics features are widely used for recognition and identification all over the world, generating large databases. In this paper a user-friendly inter…
Embedded Knowledge-based Speech Detectors for Real-Time Recognition Tasks
2006
Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of automatic speech recognition (ASR) systems are comparable to human speech recognition (HSR) only under very strict working conditions, and in general much lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to raise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as de…
Named Entity Recognition and Linking in Tweets Based on Linguistic Similarity
2017
This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applying the same strategy already presented for Question Answering (QA) by the same authors. The previous work describes a rule-based and ontology-based system that attempts to retrieve the correct answer to a query from the DBPedia ontology through a similarity measure between the query and the ontology labels. In this paper, a tweet is interpreted as a query for the QA system: both the text and the thread of a tweet are a sequence of statements that have been linked to the ontology. Provided that tweets make extensive use of informal language, the similarity measure and the underlying processes …
An Approach to Enhance Chatbot Semantic Power and Maintainability: Experiences within the FRASI Project
2012
The paper illustrates the implementation and semantic enhancement of a domain-oriented Question-Answering system based on a pattern-matching chat bot technology, developed within an industrial project, named FRASI. The main difficulty in building a KB for a chat bot is to handwrite all possible question-answer pairs that constitute the KB. The proposed approach simplifies the chat bot realization thanks to two solutions. The first one uses an ontology, which is exploited in a twofold manner: to construct dynamic answers as a result of an inference process about the domain, and to automatically populate, off-line, the chat bot KB with sentences that can be derived from the ontology, describi…