Search results for " data structure."

Time-resolved FDTD and experimental FTIR study of gold micropatch arrays for wavelength-selective mid-infrared optical coupling

2021

The work was partially supported by Sweden's innovation agency Vinnova (Large area CVD graphene-based sensors/IR-photodetectors 2020-00797) and EU CAMART2 project (European Union's Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No.739508). TY acknowledges European Regional Development Fund Project No. 1.1.1.2/VIAA/4/20/740.

Enhanced query processing for NoSQL crowdsourcing systems

2014

In this paper, we provide a novel approach for effectively and efficiently support query processing tasks in novel NoSQL crowdsourcing systems. The idea of our method is to exploit the social knowledge available from reviews about products of any kind, freely provided by customers through specialized web sites. We thus define a NoSQL database system for large collections of product reviews, where queries can be expressed in terms of natural language sentences whose answers are modeled as lists of products ranked based on the relevance of reviews w.r.t. the natural language sentences. The best ranked products in the result list can be seen as the best hints for the user based on crowd opinio…

Trusted dynamic storage for dunbar-based P2P online social networks

2014

Online Social Networks (OSNs) are becoming more and more popular in today's Internet. Distributed Online Social Networks (DOSNs), are OSNs which do not exploit a central server for storing users' data and enable users to have more control on their profile content, ensuring a higher level of privacy. The main challenge of DOSNs comes from guaranteeing availability of the data when the data owner is offline. In this paper we propose a new P2P dynamic approach to the problem of data persistence in DOSNs. By following Dunbar's approach, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Users in this set are chosen by considerin…

The Myriad Virtes of Wavelet Trees

2009

A new data structure, the wavelet tree, is analysied and discussed with particular attention to data compression

2D-Pattern Indexing

2008

Data Structures for two-dimensional pattern matching are presented and discussed.

Algorithmic paradigms for stability-based cluster validity and model selection statistical methods, with applications to microarray data analysis

2012

AbstractThe advent of high throughput technologies, in particular microarrays, for biological research has revived interest in clustering, resulting in a plethora of new clustering algorithms. However, model selection, i.e., the identification of the correct number of clusters in a dataset, has received relatively little attention. Indeed, although central for statistics, its difficulty is also well known. Fortunately, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained prominence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of pre…

Indexed Two-Dimensional String Matching

2016

A New Class of Searchable and Provably Highly Compressible String Transformations

2019

The Burrows-Wheeler Transform is a string transformation that plays a fundamental role for the design of self-indexing compressed data structures. Over the years, researchers have successfully extended this transformation outside the domains of strings. However, efforts to find non-trivial alternatives of the original, now 25 years old, Burrows-Wheeler string transformation have met limited success. In this paper we bring new lymph to this area by introducing a whole new family of transformations that have all the "myriad virtues" of the BWT: they can be computed and inverted in linear time, they produce provably highly compressible strings, and they support linear time pattern search direc…

Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks

2020

We propose a novel approach for the recommendation of possible customers (users) to advertisers (e.g., brands) based on two main aspects: (i) the comparison between On-line Social Network profiles, and (ii) neighborhood analysis on the On-line Social Network. Profile matching between users and brands is considered based on bag-of-words representation of textual contents coming from the social media, and measures such as the Term Frequency-Inverse Document Frequency are used in order to characterize the importance of words in the comparison. The approach has been implemented relying on Big Data Technologies, allowing this way the efficient analysis of very large Online Social Networks. Resul…

Clique Percolation Method: Memory Efficient Almost Exact Communities

2022

Automatic detection of relevant groups of nodes in large real-world graphs, i.e. community detection, has applications in many fields and has received a lot of attention in the last twenty years. The most popular method designed to find overlapping communities (where a node can belong to several communities) is perhaps the clique percolation method (CPM). This method formalizes the notion of community as a maximal union of $k$-cliques that can be reached from each other through a series of adjacent $k$-cliques, where two cliques are adjacent if and only if they overlap on $k-1$ nodes. Despite much effort CPM has not been scalable to large graphs for medium values of $k$. Recent work has sho…