Search results for "Semantic"

PER UNA TEORIA DEL SIGNIFICATO REALISTA RICERCHE PER UNA DIA-LOGICA DEI GIOCHI

Logica dei quantificatori dipendenti e indipendenti. Saggio critico-introduttivo alla logica filo-indipendente di Hintikka

2009

A differenza della logica tradizionale, in questa prima monografia italiana sulla logica filo-indipendente di Jaakko Hintikka, la verità logica non è la conclusione di una dimostrazione affidata a regole deduttive, ma è piuttosto il risultato della contesa dialogante tra un falsificatore (Abelardo) e un verificatore (Eloisa). In tal modo Hintikka sviluppa un linguaggio logico con una semantica basata sulla teoria dei giochi di von Neumann e Morgenstern che è in grado di descrivere, attraverso un ‘dialogo’ tra un proponente ed un opponente, l’ontologia del mondo. Che cos’è allora la verità? È forse la capacità di possedere una strategia vincente contro un opponente secondo l’attività di socr…

Automatic Dictionary Creation by Sub-symbolic Encoding of Words

2006

This paper describes a technique for automatic creation of dictionaries using sub-symbolic representation of words in cross-language context. Semantic relationship among words of two languages is extracted from aligned bilingual text corpora. This feature is obtained applying the Latent Semantic Analysis technique to the matrices representing terms co-occurrences in aligned text fragments. The technique allows to find the “best translation” according to a properly defined geometric distance in an automatically created semantic space. Experiments show an interesting correctness of 95% obtained in the best case.

Syntagmatic and Paradigmatic Associations in Information Retrieval

2003

It is shown that unconscious associative processes taking place in the memory of a searcher during the formulation of a search query in information retrieval — such as the production of free word associations and the generation of synonyms — can be simulated using statistical models that analyze the distribution of words in large text corpora. The free word associations as produced by subjects on presentation of stimulus words can be predicted by applying first-order statistics to the frequencies of word co-occurrences as observed in texts. The generation of synonyms can also be conducted on co-occurrence data but requires second-order statistics. Both approaches are compared and validated …

Graph-based exploration and clustering analysis of semantic spaces

2019

Abstract The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that …

Stit Frames as Action Systems

2015

Stit semantics gives an account of action from a certain perspective: actions are seen not as operations performed in action systems and yielding new states of affairs, but rather as selections of preexistent trajectories of the system in time. Main problems of stit semantics are recapitulated. The interrelations between stit semantics and the approach based on ordered action systems are discussed more fully.

Learning to Rank Images for Complex Queries in Concept-based Search

2018

Concept-based image search is an emerging search paradigm that utilizes a set of concepts as intermediate semantic descriptors of images to bridge the semantic gap. Typically, a user query is rather complex and cannot be well described using a single concept. However, it is less effective to tackle such complex queries by simply aggregating the individual search results for the constituent concepts. In this paper, we propose to introduce the learning to rank techniques to concept-based image search for complex queries. With freely available social tagged images, we first build concept detectors by jointly leveraging the heterogeneous visual features. Then, to formulate the image relevance, …

Representation theory treatment of measurement semantics for ratio, ordinal and nominal scales

1997

Within the scope of the representational theory a formal framework for description of semantic aspects of measurement on different scales is proposed. This is done by means of a first-order formal logical system consisting of a set of empirical predicates which play the part of a data structure in the framework, a set of operations by means of which syntactically correct statements can be formed; a set of axioms being true statements and a set of numerical statements which is an aggregation of potential measurement results carrying a meaningful load. On this basis the notation of semantic information on various scales is introduced and some common claims about the measurement semantic infor…

Artificial Intelligence + Distributed Systems = Agents

2009

The connection with Wirth’s book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic assertions, results of recent research are abridged and commented upon in line with new paradigms.…

High Locality Representations for Automated Programming

2011

We study the locality of the genotype-phenotype mapping used in grammatical evolution (GE). GE is a variant of genetic programming that can evolve complete programs in an arbitrary language using a variable-length binary string. In contrast to standard GP, which applies search operators directly to phenotypes, GE uses an additional mapping and applies search operators to binary genotypes. Therefore, there is a large semantic gap between genotypes (binary strings) and phenotypes (programs or expressions). The case study shows that the mapping used in GE has low locality leading to low performance of standard mutation operators. The study at hand is an example of how basic design principles o…