Search results for "Semantic"
showing 10 items of 941 documents
TSVD as a Statistical Estimator in the Latent Semantic Analysis Paradigm
2015
The aim of this paper is to present a new point of view that makes it possible to give a statistical interpretation of the traditional latent semantic analysis (LSA) paradigm based on the truncated singular value decomposition (TSVD) technique. We show how the TSVD can be interpreted as a statistical estimator derived from the LSA co-occurrence relationship matrix by mapping probability distributions on Riemanian manifolds. Besides, the quality of the estimator model can be expressed by introducing a figure of merit arising from the Solomonoff approach. This figure of merit takes into account both the adherence to the sample data and the simplicity of the model. In our model, the simplicity…
A Novel Visual Interface to Foster Innovation in Mechanical Engineering and Protect from Patent Infringement
2018
One of the main time and money consuming tasks in the design of industrial devices and parts is the checking of possible patent infringements. Indeed, the great number of documents to be mined and the wide variety of technical language used to describe inventions are reasons why considerable amounts of time may be needed. On the other hand, the early detection of a possible patent conflict, in addition to reducing the risk of legal disputes, could stimulate a designers' creativity to overcome similarities in overlapping patents. For this reason, there are a lot of existing patent analysis systems, each with its own features and access modes. We have designed a visual interface providing an …
AN ARCHITECTURE FOR HUMANOID ROBOT EXPRESSING EMOTIONS AND PERSONALITY
2010
In this paper we illustrate the cognitive architecture of a humanoid robot based on the proposed paradigm of Latent Semantic Analysis (LSA). The LSA approach allows the creation and the use of a data driven high-dimensional conceptual space. This paradigm is a step towards the simulation of an emotional behavior of a robot interacting with humans. The Architecture is organized in three main areas: Sub-conceptual, Emotional and Behavioral. The first area processes perceptual data coming from the sensors. The second area is the “conceptual space of emotional states” which constitutes the sub-symbolic representation of emotions. The last area activates a latent semantic behavior related to the…
Knowledge Representation in Empathic Robots-Rappresentazione della conoscenza in robot empatici
2011
In questo articolo si illustra l'architettura cognitiva di un robot umanoide basato sul paradigma della Latent Semantic Analysis (LSA). L'approccio LSA consente la creazione e l'utilizzo di un spazio concettuale multi-dimensionale e data driven. Questo paradigma è un passo verso la simulazione di un comportamento emotivo di un robot che interagisce con gli umani. L'architettura è organizzata in tre aree principali: Subconcettuale, emotivo e comportamentale. La prima area elabora i dati percettivi provenienti dai sensori. La seconda area è lo "spazio concettuale di stati emotivi" che costituisce la rappresentazione sub-simbolica di emozioni. L'ultima area attiva un comportamento semantico la…
An emotional humanoid partner
2010
In this paper we propose an emotional humanoid robot based on Latent Semantic Analysis, that exhibits an emotional behaviour in the interaction with human. Latent Semantic Analysis (LSA) paradigm is capable to encode the semantics of words using a statistical computation of a large corpus of text. We illustrate how the creation and the use of this emotional conceptual space allows the building of “Latent Semantic Behaviour” because it simulates the emotional associative capabilities of human beings. The presented approach integrates traditional knowledge representation and intuitive capabilities provided by geometric and sub-symbolic information modelling. To validate the effectiveness of t…
A Conceptual Probabilistic Model for the Induction of Image Semantics
2010
In this paper we propose a model based on a conceptual space automatically induced from data. The model is inspired to a well-founded robotics cognitive architecture which is organized in three computational areas: sub-conceptual, linguistic and conceptual. Images are objects in the sub-conceptual area, that become "knoxels" into the conceptual area. The application of the framework grants the automatic emerging of image semantics into the linguistic area. The core of the model is a conceptual space induced automatically from a set of annotated images that exploits and mixes different information concerning the set of images. Multiple low level features are extracted to represent images and…
A Semantic Similarity Measure for the SIMS Framework
2008
The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …
Unifying Textual and Visual Cues for Content-Based Image Retrieval on the World Wide Web
1999
A system is proposed that combines textual and visual statistics in a single index vector for content-based search of a WWW image database. Textual statistics are captured in vector form using latent semantic indexing based on text in the containing HTML document. Visual statistics are captured in vector form using color and orientation histograms. By using an integrated approach, it becomes possible to take advantage of possible statistical couplings between the content of the document (latent semantic content) and the contents of images (visual statistics). The combined approach allows improved performance in conducting content-based search. Search performance experiments are reported for…
An A* Based Semantic Tokenizer for Increasing the Performance of Semantic Applications
2013
Semantic Applications (SAs) makes use of ontolo- gies and their performance can depend on the syntactic labels of the modeled entities; even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A* based search algorithm; the A* functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.
An Innovative Statistical Tool for Automatic OWL-ERD Alignment
2016
Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corre…