Encouraged by a significant improvement over LSI (latent semantic indexing) approach in textual information retrieval of the DLSI (differential latent semantic indexing) approach which technically makes use of two term vectors for each document, we have proposed a concept of stereo, or multiperspective, document representation, which is expected to be effective for most of textual information r...

The textual description of video sequences exploits conceptual knowledge about the behavior of depicted agents. An explicit representation of such behavioral knowledge facilitates not only the textual description of video evaluation results, but can also be used for the inverse task of generating synthetic image sequences from textual descriptions of dynamic scenes. Moreover, it is shown here t...

This paper presents how the TAAABLE project addresses the textual case-based reasoning challenge of the CCC, thanks to a combination of principles, methods, and technologies of various fields of knowledge-based system technologies, namely CBR, ontology engineering (manual and semi-automatic), data and text-mining using textual resources of the Web, text annotation (used as an indexing technique...

GIMPLE is the machine-independent intermediate representation used in modern GCC releases (post version 4.0). While the GIMPLE API for code generation and manipulation has matured over time, the corresponding textual representation is yet to be in a stable form. This issue hampers many serious efforts for code generation from and to GIMPLE. Good candidates for the textual representation seem to...

Existing parsers for textual model representation formats such as XMI and HUTN are unforgiving and fail upon even the smallest inconsistency between the structure and naming of metamodel elements and the contents of serialised models. In this paper, we demonstrate how a flexible parsing approach can transparently and automatically resolve a number of these inconsistencies, and how it can eventu...

In this paper, we address the problem for predicting cQA answer quality as a classification task. We propose a multimodal deep belief nets based approach that operates in two stages: First, the joint representation is learned by taking both textual and non-textual features into a deep learning network. Then, the joint representation learned by the network is used as input features for a linear ...

Fine-grained image classification is to recognize hundreds of subcategories belonging to the same basic-level category, which is a highly challenging task due to the quite subtle visual distinctions among similar subcategories. Most existing methods generally learn part detectors to discover discriminative regions for better classification accuracy. However, not all localized parts are benefici...

Statement of the problem. The results interdisciplinary studies show that aging process was causelessly associated with words decline, vulnerability and has a gender marking. relationship between these two identities is complex, as linguistic research, it not been studied to sufficient extent yet, does have satisfactory theoretical foundation. purpose article analyze lexical units ageist semant...

This paper presents a graphical representation for the Formal Description Technique Estelle, which has up until now been restricted to a textual syntax based on the general programming language Pascal. The graphical syntax and semantics of the representation are fully descriptive of a general Estelle system and complies with the ISO Estelle standard ISO97]. This representation aims to become a ...