Similarity in recognition processes used for bodies and faces: Bodies show caricature effects

Because faces and bodies share some abstract perceptual features, we hypothesised that similar recognition processes might be used for both. We investigated whether similar caricature effects to those found in facial identity and expression recognition could be found in the recognition of individual bodies and socially meaningful body positions. Participants were trained to name four body positions (anger, fear, disgust, sadness) and four individuals (in a neutral position). We then tested their recognition of extremely caricatured, moderately caricatured, anticaricatured, and undistorted images of each stimulus. Consistent with caricature effects found in face recognition, moderately caricatured representations of individuals' bodies were recognised more accurately than undistorted and extremely caricatured representations. No significant difference was found between participants' recognition of extremely caricatured, moderately caricatured, or undistorted body position line-drawings. AU anti-caricatured representations were named significandy less accurately than the veridical stimuli. Similar mental representations may be used for both bodies and faces.

Exploring composite acoustic features for efficient music similarity query

Music similarity query based on acoustic content is becoming important with the ever-increasing growth of the music information from emerging applications such as digital libraries and WWW. However, relative techniques are still in their infancy and much less than satisfactory. In this paper, we present a novel index structure, called Composite Feature tree, CF-tree, to facilitate efficient content-based music search adopting multiple musical features. Before constructing the tree structure, we use PCA to transform the extracted features into a new space sorted by the importance of acoustic features. The CF-tree is a balanced multi-way tree structure where each level represents the data space at different dimensionalities. The PCA transformed data and reduced dimensions in the upper levels can alleviate suffering from dimensionality curse. To accurately mimic human perception, an extension, named CF+-tree, is proposed, which further applies multivariable regression to determine the weight of each individual feature. We conduct extensive experiments to evaluate the proposed structures against state-of-art techniques. The experimental results demonstrate superiority of our technique.

MQL: A powerful extension to OCL for MOF queries

The Meta-Object Facility (MOF) provides a standardized framework for object-oriented models. An instance of a MOF model contains objects and links whose interfaces are entirely derived from that model. Information contained in these objects can be accessed directly, however, in order to realize the Model-Driven Architecture@trade; (MDA), we must have a mechanism for representing and evaluating structured queries on these instances. The MOF Query Language (MQL) is a language that extends the UML's Object Constraint Language (OCL) to provide more expressive power, such as higher-order queries, parametric polymorphism and argument polymorphism. Not only do these features allow more powerful queries, but they also encourage a greater degree of modularization and re-use, resulting in faster prototyping and facilitating automated integrity analysis. This paper presents an overview of the motivations for developing MQL and also discusses its abstract syntax, presented as a MOF model, and its semantics

From marine ecology to crime analysis: improving the detection of serial sexual offences using a taxonomic similarity measure

Jaccard has been the choice similarity metric in ecology and forensic psychology for comparison of sites or offences, by species or behaviour. This paper applies a more powerful hierarchical measure - taxonomic similarity (s), recently developed in marine ecology - to the task of behaviourally linking serial crime. Forensic case linkage attempts to identify behaviourally similar offences committed by the same unknown perpetrator (called linked offences). s considers progressively higher-level taxa, such that two sites show some similarity even without shared species. We apply this index by analysing 55 specific offence behaviours classified hierarchically. The behaviours are taken from 16 sexual offences by seven juveniles where each offender committed two or more offences. We demonstrate that both Jaccard and s show linked offences to be significantly more similar than unlinked offences. With up to 20% of the specific behaviours removed in simulations, s is equally or more effective at distinguishing linked offences than where Jaccard uses a full data set. Moreover, s retains significant difference between linked and unlinked pairs, with up to 50% of the specific behaviours removed. As police decision-making often depends upon incomplete data, s has clear advantages and its application may extend to other crime types. Copyright © 2007 John Wiley & Sons, Ltd.

Measuring the influence of similarity on category-specific effects

There is evidence for both advantages and disadvantages in normal recognition of living over nonliving things. This paradox has been attributed to high levels of perceptual similarity within living categories having a different effect on performance in different contexts. However, since living things are intrinsically more similar to each other, previous studies could not determine whether the various category effects were due to perceptual similarity, or to other characteristics of living things. We used novel animal and vehicle stimuli that were matched for similarity to measure the influence of perceptual similarity in different contexts. We found that displaying highly similar objects in blocked sets reduced their perceived similarity, eliminating the detrimental effect on naming performance. Experiment 1 demonstrated a disadvantage for highly similar objects in name learning and name verification using mixed groups of similar and dissimilar animals and vehicles. Experiment 2 demonstrated no disadvantage for the same highly similar objects when they were blocked, e.g., similar animals presented alone. Thus, perceptual similarity, rather than other characteristics particular to living things, is affected by context, and could create apparent category effects under certain testing conditions.

Document retrieval based on a cognitive model of dialogue

Owing to the rise in the volume of literature, problems arise in the retrieval of required information. Various retrieval strategies have been proposed, but most of that are not flexible enough for their users. Specifically, most of these systems assume that users know exactly what they are looking for before approaching the system, and that users are able to precisely express their information needs according to l aid- down specifications. There has, however, been described a retrieval program THOMAS which aims at satisfying incompletely- defined user needs through a man- machine dialogue which does not require any rigid queries. Unlike most systems, Thomas attempts to satisfy the user's needs from a model which it builds of the user's area of interest. This model is a subset of the program's "world model" - a database in the form of a network where the nodes represent concepts since various concepts have various degrees of similarities and associations, this thesis contends that instead of models which assume equal levels of similarities between concepts, the links between the concepts should have values assigned to them to indicate the degree of similarity between the concepts. Furthermore, the world model of the system should be structured such that concepts which are related to one another be clustered together, so that a user- interaction would involve only the relevant clusters rather than the entire database such clusters being determined by the system, not the user. This thesis also attempts to link the design work with the current notion in psychology centred on the use of the computer to simulate human cognitive processes. In this case, an attempt has been made to model a dialogue between two people - the information seeker and the information expert. The system, called Thomas-II, has been implemented and found to require less effort from the user than Thomas.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

Goal detection from natural language queries

This paper aims to identify the communication goal(s) of a user's information-seeking query out of a finite set of within-domain goals in natural language queries. It proposes using Tree-Augmented Naive Bayes networks (TANs) for goal detection. The problem is formulated as N binary decisions, and each is performed by a TAN. Comparative study has been carried out to compare the performance with Naive Bayes, fully-connected TANs, and multi-layer neural networks. Experimental results show that TANs consistently give better results when tested on the ATIS and DARPA Communicator corpora.

Document similarity:a new measure using OWA

In this paper, we propose a new similarity measure to compute the pair-wise similarity of text-based documents based on patterns of the words in the documents. First we develop a kappa measure for pair-wise comparison of documents then we use ordered weighting averaging operator to define a document similarity measure for a set of documents.

Cross ontology query answering on the semantic web:an initial evaluation

PowerAqua is a Question Answering system, which takes as input a natural language query and is able to return answers drawn from relevant semantic resources found anywhere on the Semantic Web. In this paper we provide two novel contributions: First, we detail a new component of the system, the Triple Similarity Service, which is able to match queries effectively to triples found in different ontologies on the Semantic Web. Second, we provide a first evaluation of the system, which in addition to providing data about PowerAqua's competence, also gives us important insights into the issues related to using the Semantic Web as the target answer set in Question Answering. In particular, we show that, despite the problems related to the noisy and incomplete conceptualizations, which can be found on the Semantic Web, good results can already be obtained.

AquaLog : an ontology-driven question answering system for organizational semantic intranets

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.