In the era of big data, the volume of digital data is increasing rapidly, causing new challenges for investigators to examine the same in a reasonable amount of time. A major requirement of modern forensic investigation is the ability to perform automatic filtering of correlated data, and thereby reducing and focusing the manual effort of the investigator. Approximate matching is a technique to...

We introduce a concept of similarity between vertices of directed graphs. Let GA and GB be two directed graphs with, respectively, nA and nB vertices. We define an nB ×nA similarity matrix S whose real entry sij expresses how similar vertex j (in GA) is to vertex i (in GB): we say that sij is their similarity score. The similarity matrix can be obtained as the limit of the normalized even itera...

This article presents a method for computing Likelihood Ratios (LR) from multimodal score distributions produced by an Automated Fingerprint Identification System (AFIS) feature extraction and comparison algorithm. The AFIS algorithm used to compare fingermarks and fingerprints was primarily developed for forensic investigation rather than for forensic evaluation. The computation of the scores ...

Abstract. We introduce a concept of similarity between vertices of directed graphs. Let GA and GB be two directed graphs with respectively nA and nB vertices. We define a nA × nB similarity matrix S whose real entry sij expresses how similar vertex i (in GA) is to vertex j (in GB) : we say that sij is their similarity score. In the special case where GA = GB = G, the score sij is the similarity...

Abstract. We introduce a concept of similarity between vertices of directed graphs. Let GA and GB be two directed graphs with respectively nA and nB vertices. We define a nB × nA similarity matrix S whose real entry sij expresses how similar vertex j (in GA) is to vertex i (in GB) : we say that sij is their similarity score. The similarity matrix can be obtained as the limit of the normalized e...

Conventional relevance feedback schemes may not be suitable to all practical applications of content based image retrieval (CBIR), since most ordinary users like to complete their search in a single interaction, especially on web search. In this paper, we explore a new approach based on multifeature similarity score fusion using genetic algorithm. Single feature describes image content only fro...

This paper describes the system that was submitted in the *SEM 2013 Semantic Textual Similarity shared task. The task aims to find the similarity score between a pair of sentences. We describe a Universal Networking Language (UNL) based semantic extraction system for measuring the semantic similarity. Our approach combines syntactic and word level similarity measures along with the UNL based se...

MOTIVATION The similarity of two biological sequences has traditionally been assessed within the well-established framework of alignment. Here we focus on the task of identifying functional relationships between cis-regulatory sequences that are non-orthologous or greatly diverged. 'Alignment-free' measures of sequence similarity are required in this regime. RESULTS We investigate the use of ...

The problem of link prediction has attracted considerable recent attention from various domains such as sociology, anthropology, information science, and computer sciences. A link prediction algorithm is proposed based on link similarity score propagation by a random walk in networks with nodes attributes. In the algorithm, each link in the network is assigned a transmission probability accordi...

In Semantic Textual Similarity, systems rate the degree of semantic equivalence on a graded scale from 0 to 5, with 5 being the most similar. For the English subtask, we present a system which relies on several resources for token-to-token and phrase-to-phrase similarity to build a data-structure which holds all the information, and then combine the information to get a similarity score. We als...