Search results for "Similarity"
showing 10 items of 474 documents
Detecting self-similarity in surface microstructures
2000
The relative configurational entropy per cell as a function of length scale is a sensitive detector of spatial self-similarity. For Sierpinski carpets the equally separated peaks of the above function appear at the length scales that depend on the kind of the carpet. These peaks point to the presence of self-similarity even for randomly perturbed initial fractal sets. This is also demonstrated for the model population of particles diffusing over the surface considered by Van Siclen, Phys. Rev. E 56 (1997) 5211. These results allow the subtle self-similarity traces to be explored.
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 …
Movie Script Similarity Using Multilayer Network Portrait Divergence
2020
International audience; This paper addresses the question of movie similarity through multilayer graph similarity measures. Recent work has shown how to construct multilayer networks using movie scripts, and how they capture different aspects of the stories. Based on this modeling, we propose to rely on the multilayer structure and compute different similarities, so we may compare movies, not from their visual content, summary, or actors, but actually from their own storyboard. We propose to do so using “portrait divergence”, which has been recently introduced to compute graph distances from summarizing graph characteristics. We illustrate our approach on the series of six Star Wars movies.
Top-k String Similarity Joins
2020
Top-k joins have been extensively studied in relational databases as ranking operations when every object has, among others, at least one ranking attribute. However, the focus has mostly been the case when the join attributes are of primitive data types (e.g., numerical values) and the join predicate is equality. In this work, we consider string objects assigned such ranking attributes or simply scores. Given two collection of string objects and a string similarity measure (e.g., the Edit distance), we introduce the top-k string similarity join () which returns k sufficiently similar pairs of objects with respect to a similarity threshold ϵ, which have the highest combined score computed by…
LeSSS: Learned Shared Semantic Spaces for Relating Multi-Modal Representations of 3D Shapes
2015
In this paper, we propose a new method for structuring multi-modal representations of shapes according to semantic relations. We learn a metric that links semantically similar objects represented in different modalities. First, 3D-shapes are associated with textual labels by learning how textual attributes are related to the observed geometry. Correlations between similar labels are captured by simultaneously embedding labels and shape descriptors into a common latent space in which an inner product corresponds to similarity. The mapping is learned robustly by optimizing a rank-based loss function under a sparseness prior for the spectrum of the matrix of all classifiers. Second, we extend …
Learning Similarity Scores by Using a Family of Distance Functions in Multiple Feature Spaces
2017
There exist a large number of distance functions that allow one to measure similarity between feature vectors and thus can be used for ranking purposes. When multiple representations of the same object are available, distances in each representation space may be combined to produce a single similarity score. In this paper, we present a method to build such a similarity ranking out of a family of distance functions. Unlike other approaches that aim to select the best distance function for a particular context, we use several distances and combine them in a convenient way. To this end, we adopt a classical similarity learning approach and face the problem as a standard supervised machine lea…
Trend Following with Momentum Versus Moving Average: A Tale of Differences
2018
Despite the ever-growing interest in trend following and a series of publications in academic journals, there is still a great shortage of theoretical results on the properties of trend following rules. Our paper fills this gap by comparing and contrasting the two most popular trend following rules, the Momentum (MOM) and Moving Average (MA) rules, from a theoretical perspective. Our approach is based on the return-based formulation of trading rules and modelling the price trends by an autoregressive return process. We provide theoretical results on the similarity between various trend following rules and the forecast accuracy of trading rules. Our results show that the similarity between t…
Portable central baffle flume
2022
This paper investigated the hydraulic characteristics of the triangular central baffle (TCB) flume. Laboratory tests were carried out to determine the flume dimensions. The field applicability of the proposed portable device was examined by on-farm installation. According to the laboratory tests, when the contraction ratio, r, was less than 0.39, the flow capacity was not affected by the ratio between the flume’s floor height and the throat width. The laboratory analysis also showed that there was no significant effect of installing an entrance ramp on the stage-discharge relationship for r<0.39, while the entrance ramp increased the discharge capacity for r>0.39. The stage-discharge …
Intruder Pattern Identification
2008
This paper considers the problem of intrusion detection in information systems as a classification problem. In particular the case of masquerader is treated. This kind of intrusion is one of the more difficult to discover because it may attack already open user sessions. Moreover, this problem is complex because of the large variability of user models and the lack of available data for the learning purpose. Here, flexible and robust similarity measures, suitable also for non-numeric data, are defined, they will be incorporated on a one-class training K N N and compared with several classification methods proposed in the literature using the Masquerading User Data set (www.schonlau.net) repr…