Acta Universitatis Sapientiae Informatica最新文献_第9页

Connecting the Last.fm Dataset to LyricWiki and MusicBrainz. Lyrics-based experiments in genre classification 连接最后一个。fm数据集到LyricWiki和MusicBrainz。基于歌词的体裁分类实验

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-12-01 DOI: 10.2478/ausi-2018-0009

Z. Bodó, Eszter Szilágyi

{"title":"Connecting the Last.fm Dataset to LyricWiki and MusicBrainz. Lyrics-based experiments in genre classification","authors":"Z. Bodó, Eszter Szilágyi","doi":"10.2478/ausi-2018-0009","DOIUrl":"https://doi.org/10.2478/ausi-2018-0009","url":null,"abstract":"Abstract Music information retrieval has lately become an important field of information retrieval, because by profound analysis of music pieces important information can be collected: genre labels, mood prediction, artist identification, just to name a few. The lack of large-scale music datasets containing audio features and metadata has lead to the construction and publication of the Million Song Dataset (MSD) and its satellite datasets. Nonetheless, mainly because of licensing limitations, no freely available lyrics datasets have been published for research. In this paper we describe the construction of an English lyrics dataset based on the Last.fm Dataset, connected to LyricWiki’s database and MusicBrainz’s encyclopedia. To avoid copyright issues, only the URLs to the lyrics are stored in the database. In order to demonstrate the eligibility of the compiled dataset, in the second part of the paper we present genre classification experiments with lyrics-based features, including bagof-n-grams, as well as higher-level features such as rhyme-based and statistical text features. We obtained results similar to the experimental outcomes presented in other works, showing that more sophisticated textual features can improve genre classification performance, and indicating the superiority of the binary weighting scheme compared to tf–idf.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"1 1","pages":"158 - 182"},"PeriodicalIF":0.3,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87719868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Statistical complexity of the quasiperiodical damped systems 准周期阻尼系统的统计复杂性

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-12-01 DOI: 10.2478/ausi-2018-0012

Á. Fülöp

引用次数: 0

Minimum covering reciprocal distance signless Laplacian energy of graphs 图的最小覆盖倒数距离无符号拉普拉斯能量

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-12-01 DOI: 10.2478/ausi-2018-0011

A. Alhevaz, M. Baghipur, E. Hashemi, Y. Alizadeh

{"title":"Minimum covering reciprocal distance signless Laplacian energy of graphs","authors":"A. Alhevaz, M. Baghipur, E. Hashemi, Y. Alizadeh","doi":"10.2478/ausi-2018-0011","DOIUrl":"https://doi.org/10.2478/ausi-2018-0011","url":null,"abstract":"Abstract Let G be a simple connected graph. The reciprocal transmission Tr′G(ν) of a vertex ν is defined as TrG′(ν)=∑u∈V(G)1dG(u,ν), u≠ν. $${rm{Tr}}_{rm{G}}^prime ({rm{nu }}) = sumlimits_{{rm{u}} in {rm{V}}(G)} {{1 over {{{rm{d}}_{rm{G}}}(u,{rm{nu }})}}{rm{u}} ne {rm{nu }}.} $$ The reciprocal distance signless Laplacian (briefly RDSL) matrix of a connected graph G is defined as RQ(G)= diag(Tr′ (G)) + RD(G), where RD(G) is the Harary matrix (reciprocal distance matrix) of G and diag(Tr′ (G)) is the diagonal matrix of the vertex reciprocal transmissions in G. In this paper, we investigate the RDSL spectrum of some classes of graphs that are arisen from graph operations such as cartesian product, extended double cover product and InduBala product. We introduce minimum covering reciprocal distance signless Laplacian matrix (or briey MCRDSL matrix) of G as the square matrix of order n, RQC(G) := (qi;j), qij={1+Tr′(νi)ifi=jandνi∈CTr′(νi)ifi=jandνi∉C1d(νi,νj)otherwise $${{rm{q}}_{{rm{ij}}}} = left{ {matrix{ {1 + {rm{Tr}}prime ({{rm{nu }}_{rm{i}}})} & {{rm{if}}} & {{rm{i = j}}} & {{rm{and}}} & {{{rm{nu }}_{rm{i}}} in {rm{C}}} cr {{rm{Tr}}prime ({{rm{nu }}_{rm{i}}})} & {{rm{if}}} & {{rm{i = j}}} & {{rm{and}}} & {{{rm{nu }}_{rm{i}}} notin {rm{C}}} cr {{1 over {{rm{d(}}{{rm{nu }}_{rm{i}}},{{rm{nu }}_{rm{j}}})}}} & {{rm{otherwise}}} & {} & {} & {} cr } } right.$$ where C is a minimum vertex cover set of G. MCRDSL energy of a graph G is defined as sum of eigenvalues of RQC. Extremal graphs with respect to MCRDSL energy of graph are characterized. We also obtain some bounds on MCRDSL energy of a graph and MCRDSL spectral radius of 𝒢, which is the largest eigenvalue of the matrix RQC (G) of graphs.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"40 12","pages":"218 - 240"},"PeriodicalIF":0.3,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72469105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Exact fit problem generator for cutting and packing, revisiting of the upper deck placement algorithm 切割和包装的精确拟合问题生成器，重新审视上层甲板放置算法

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI: 10.2478/ausi-2018-0005

Levente Filep, L. Illyés

{"title":"Exact fit problem generator for cutting and packing, revisiting of the upper deck placement algorithm","authors":"Levente Filep, L. Illyés","doi":"10.2478/ausi-2018-0005","DOIUrl":"https://doi.org/10.2478/ausi-2018-0005","url":null,"abstract":"Abstract Problem generators are practical solutions for generating a set of inputs to specific problems. These inputs are widely used for testing, comparing and optimizing placement algorithms. The problem generator presented in this paper fills the gap in the area of 2D Cutting & Packing as the sum of the area of the small objects is equal to the area of the Large Object and has at least one perfect solution. In this paper, the already proposed Upper Deck algorithm is revisited and used to test the proposed generator outputs. This algorithm bypasses the dead area problem that occurs in most of all well-known strategies of the 2D Single Knapsack Problem where we have a single large rectangle to cover with small, heterogeneous rectangle shapes, whom total area exceeds the large object’s area. The idea of placing the small shapes in a free corner simplifies and speeds the placement algorithm as only the available angles are checked for possible placements, and collision detection only requires the checking of corners and edges of the placed shape. Since the proposed generator output has at least one exact solution, a series of optimization performed on the algorithm is also presented.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"90 1","pages":"73 - 85"},"PeriodicalIF":0.3,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86153996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A survey on sentiment classification algorithms, challenges and applications 情感分类算法、挑战及应用综述

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI: 10.2478/ausi-2018-0004

Muhammad Rizwan Rashid Rana, Asif Nawaz, J. Iqbal

引用次数: 6

Low and high grade glioma segmentation in multispectral brain MRI data 脑MRI多光谱数据中低级别和高级别胶质瘤的分割

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI: 10.2478/ausi-2018-0007

L. Szilágyi, David Iclanzan, Zoltán Kapás, Z. Szabó, Ágnes Győrfi, László Lefkovits

{"title":"Low and high grade glioma segmentation in multispectral brain MRI data","authors":"L. Szilágyi, David Iclanzan, Zoltán Kapás, Z. Szabó, Ágnes Győrfi, László Lefkovits","doi":"10.2478/ausi-2018-0007","DOIUrl":"https://doi.org/10.2478/ausi-2018-0007","url":null,"abstract":"Abstract Several hundreds of thousand humans are diagnosed with brain cancer every year, and the majority dies within the next two years. The chances of survival could be easiest improved by early diagnosis. This is why there is a strong need for reliable algorithms that can detect the presence of gliomas in their early stage. While an automatic tumor detection algorithm can support a mass screening system, the precise segmentation of the tumor can assist medical staff at therapy planning and patient monitoring. This paper presents a random forest based procedure trained to segment gliomas in multispectral volumetric MRI records. Beside the four observed features, the proposed solution uses 100 further features extracted via morphological operations and Gabor wavelet filtering. A neighborhood-based post-processing was designed to regularize and improve the output of the classifier. The proposed algorithm was trained and tested separately with the 54 low-grade and 220 high-grade tumor volumes of the MICCAI BRATS 2016 training database. For both data sets, the achieved accuracy is characterized by an overall mean Dice score > 83%, sensitivity > 85%, and specificity > 98%. The proposed method is likely to detect all gliomas larger than 10 mL.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"23 1","pages":"110 - 132"},"PeriodicalIF":0.3,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85677132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

On the use of model transformation for the automation of product derivation process in SPL 模型转换在SPL产品派生过程自动化中的应用

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI: 10.2478/ausi-2018-0003

Nesrine Lahiani, Djamal Bennouar

引用次数: 0

Modular strategic SMT solving with SMT-RAT 基于SMT- rat的模块化策略SMT求解

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-08-01 DOI: 10.2478/ausi-2018-0001

Gereon Kremer, E. Ábrahám

引用次数: 4

Hierarchical clustering with deep Q-learning 基于深度q -学习的分层聚类

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2018-05-28 DOI: 10.2478/ausi-2018-0006

Richard Forster, A. Fulop

引用次数: 0

Hierarchical kt jet clustering for parallel architectures 并行体系结构的分层kt射流聚类

IF 0.3

Acta Universitatis Sapientiae Informatica Pub Date : 2017-12-20 DOI: 10.1515/ausi-2017-0012

Richard Forster, Á. Fülöp

{"title":"Hierarchical kt jet clustering for parallel architectures","authors":"Richard Forster, Á. Fülöp","doi":"10.1515/ausi-2017-0012","DOIUrl":"https://doi.org/10.1515/ausi-2017-0012","url":null,"abstract":"Abstract The reconstruction and analyze of measured data play important role in the research of high energy particle physics. This leads to new results in both experimental and theoretical physics. This requires algorithm improvements and high computer capacity. Clustering algorithm makes it possible to get to know the jet structure more accurately. More granular parallelization of the kt cluster algorithms was explored by combining it with the hierarchical clustering methods used in network evaluations. The kt method allows to know the development of particles due to the collision of high-energy nucleus-nucleus. The hierarchical clustering algorithms works on graphs, so the particle information used by the standard kt algorithm was first transformed into an appropriate graph, representing the network of particles. Testing was done using data samples from the Alice offine library, which contains the required modules to simulate the ALICE detector that is a dedicated Pb-Pb detector. The proposed algorithm was compared to the FastJet toolkit's standard longitudinal invariant kt implementation. Parallelizing the standard non-optimized version of this algorithm utilizing the available CPU architecture proved to be 1:6 times faster, than the standard implementation, while the proposed solution in this paper was able to achieve a 12 times faster computing performance, also being scalable enough to efficiently run on GPUs.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"8 1","pages":"195 - 213"},"PeriodicalIF":0.3,"publicationDate":"2017-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75889962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1