Semantic Clustering of Genomic Documents using GO Terms as Feature Set

The biological databases generate huge volume of genomics and proteomics data. The sequence information is used by researches to find similarity of genes, proteins and to find other related information. The genomic sequence database consists of large number of attributes as annotations, represented for defining the sequences in Xml format. It is necessary to have proper mechanism to group the documents for information retrieval. Data mining techniques like clustering and classification methods can be used to group the documents. The objective of the paper is to analyze the set of keywords which can be represented as features for grouping the documents semantically. This paper focuses on clustering genomic documents based on both structural and content similarity .The structural similarity is found using structural path between the documents. The semantic similarity is found for the structurally similar documents. We have proposed a methodology to cluster the genomic documents using sequence attributes without using the sequence data. The sequence attributes for genomic documents are analyzed using Filter based feature selection methods to find the relevant feature set for grouping the similar documents. Based on the attribute ranking we have clustered the similar documents using All Keyword approach (KBA) and GO Terms based approach (GOTA). The experimental results of the clusters are validated for two approaches by inferring biological meaning using Gene Ontology. From the results it was inferred that all keywords based approach grouped documents based on the semantic meaning of Gene Ontology terms. The GO terms based approach grouped larger number of documents without considering any other keywords, which is semantically relevant which results in reducing the complexity of the attributes considered. We claim that using GO terms can alone be used as features set to group genomic documents with high similarity

The C@merata Task at MediaEval 2015: Natural Language Queries on Classical Music Scores

This was the second year of the C@merata task [16,1] which relates natural language processing to music inform ation retrieval. Participants each build a system which takes as input a query and a music score and produces as output one or more ma tching passages in the score. This year, questions were mo re difficult and scores were more complex. Participants were the same as last year and once again CLAS was the best with a Beat F-Score of 0.620

The C@merata Task at MediaEval 2015: Natural Language Queries on Classical Music Scores

ABSTRACT This was the second year of the C@merata tas

Information technological aspects in the field of music. Overview

Uurimuse põhieesmärgiks on anda lugejale ülevaade nootide (noodilehtede) ettevalmistamist ja muusika esitamist toetavatest tarkvarapakettidest ning tutvustada olulisemaid aspekte, mis on seotud nende rakendamisega muusikavallas. Üksikasjaliku ülevaate esitab töö tulemusena valminud veebisõelmete andmebaas koos seda esitava veebirakendusega, mis sisaldab nimetatud tarkvarapakette iseloomustavaid kirjeid. Töö tekstiline osa, st dokument, kirjeldab kokkuvõtlikult olulisemaid aspekte koos mõningate tarkvaraliste näidetega. Osutub, et kõige rohkem leidub internetis noodigraafika töötlemise ning diginoodiks teisendamise vahendeid – vastavalt 98 ja 13 rakendust. Nende valdkondadega seotud töö jaotistes sätestatakse erinevad kriteeriumid, mida nimetatud rakenduste andmebaasi kandmisel arvesse võeti, aga ka meetodeid ja probleeme, millega vastavate rakenduste kasutamisel arvestada tuleks. Uurimust alustades oli üks esmaseid eesmärke koguda võimalikult palju informatsiooni intelligentsete muusikaseadmete, eelkõige elektroonilis-intelligentsete noodipultide kohta. Paraku leidub just nimelt selles valdkonnas kõige vähem vahendeid – kokku vaid 4 rakendust, millest reaalselt kasutatav on vaid üks. Töös kirjeldatakse rakenduste võimalikke omavahelisi võrdlusmomente, analüüsitakse vaadeldava valdkonna nüansse ning tutvustatakse arenguperspektiive. Informatiivsuse huvides on esitletud aga ka tarkvarakomponente ja -pakette (sh raamistikke), mis kaudselt toetavad nootide (noodilehtede) ettevalmistamist ning muusika esitamist – kokku 55 kirjet. Lisaks kirjeldatakse muusikaõpet toetavaid vahendeid. Nendest on andmebaasi kantud kokku 14 rakendust. Antakse põgus ülevaade olemasolevatest huvitavamatest noodikogudest ning nende kasutamisvõimalustest; andmebaasi lisatud vastavalt 13 kirjet. Tutvustatakse aga ka uurimuse kontekstiga seotud bibliograafiat ning ühte tuntumat konverentsiseeriat (ISMIR), mille raames on paljud publikatsioonid valminud. Publikatsioonide loetelu on samuti lisatud töö käigus valminud andmebaasi – kokku 113 kirjet. Arvestades, et pakettide kasutajaliidesed on reeglina ingliskeelsed, on koostatud vastav inglise-eesti terminisõnastik.The main purpose of this thesis is to give an overview of the existing software packages and tools, oriented towards the simplification of musicians everyday work. Since the field is quite extensive, only a subset of the available software has been taken into account – mainly programs designed to support preparing and interpreting sheet music. The thesis is divided into two major components – a database (appended on a CD), which contains all the information about the collected data (software, hardware, related bibliography, etc) and the document itself, where the criterions for comparing the software packages are listed and explained together with some illustrative examples. The first two chapters of the document are dedicated to the ways of generating sheet music – describing and comparing the different software tools for displaying and editing sheet music using note graphics software. Also, an overview of intelligent music stands, which is still an underdeveloped branch in this field, is given. The third chapter of the document describes aspects of using music software as a learning intent complemented with some examples of a freeware program. Additionally, a slight overview of digital (sheet)music archives together with some interesting examples is given in the fourth chapter. Also, the field-specific bibliography (comprising years 1989-2012) is presented in the fifth chapter. In consideration of the fact that almost all user interfaces of the software packages use English language, an illustrated English-Estonian dictionary of relevant terms is appended. The database contains 184 entries of topic-related software packages – 4 intelligent music stand applications, 13 digital sheet music converter applications, 98 score editors, 14 study assistant applications and 55 miscellaneous applications; 13 digital note archives and 113 publications

Relating Natural Language Text to Musical Passages

There is a vast body of musicological literature containing detailed analyses of musical works. These texts make frequent references to musical passages in scores by means of natural language phrases. Our long- term aim is to investigate whether these phrases can be linked automatically to the musical passages to which they refer. As a first step, we have organised for two years running a shared evaluation in which participants must develop software to identify passages in a MusicXML score based on a short noun phrase in English. In this paper, we present the rationale for this work, discuss the kind of references to musical passages which can occur in actual scholarly texts, describe the first two years of the evaluation and finally appraise the results to establish what progress we have made

A system for the analysis of musical data

The role of music analysis is to enlighten our understanding of a piece of music. The role of musical performance analysis is to help us understand how a performer interprets a piece of music. The current work provides a tool which combines music analysis with performance analysis. By combining music and performance analysis in one system new questions can be asked of a piece of music: how is the structure of a piece reflected in the performance and how can the performance enlighten our understanding of the piece's structure? The current work describes a unified database which can store and present musical score alongside associated performance data and musical analysis. Using a general purpose representation language, Performance Mark-up Language (PML), aspects of performance are recorded and analysed. Data thus acquired from one project is made available to others. Presentation involves high-quality scores suitably annotated with the requested information. Such output is easily and directly accessible to musicians, performance scientists and analysts. We define a set of data structures and operators which can operate on musical pitch and musical time, and use them to form the basis of a query language for a musical database. The database can store musical information (score, gestural data, etc.). Querying the database results in annotations of the musical score. The database is capable of storing musical score information and performance data and cross-referencing them. It is equipped with the necessary primitives to execute music-analytical queries, and highlight notes identified from the score and display performance data alongside the score

Music Encoding Conference Proceedings 2021, 19–22 July, 2021 University of Alicante (Spain): Onsite & Online

Este documento incluye los artículos y pósters presentados en el Music Encoding Conference 2021 realizado en Alicante entre el 19 y el 22 de julio de 2022.Funded by project Multiscore, MCIN/AEI/10.13039/50110001103

An empirical investigation of the concept of memes in music using mass data analysis of string quartets

Dawkins introduced the concept of the meme as the cultural equivalent to the gene (1989, pp. 189-201). To illustrate the concept, Dawkins cited ‘tunes, ideas, catch-phrases, clothes, fashions, ways of making pots or of building arches’ (1989, p. 192) as examples of memes. All of Dawkins’ examples are elements of culture that have evolved over time. Because music is a part of culture, then under Dawkins’ hypothesis, memes should exist in music. After all, the first of Dawkins’ examples was a ‘tune’. Jan expanded on Dawkins’ ideas with a thorough investigation into memes in music (2007). This was done on a number of different levels within music, from melodic lines to overall structure, using a range of examples within music. Whilst providing a strong case for memes, Jan was not able to provide evidence from an analysis encompassing a large dataset of music. However, Jan does provide a number of possible methodologies for analysing memes in music, including investigating memes across time periods using single lines of notes (2007, p. 211). The present research expands on Jan’s suggested methodology by looking at short monophonic three- to eleven-note patterns in music across five different non-traditional musicological time periods within a large dataset of string quartets. A search for memes in music is conducted using a range of scores. These are converted to MusicXML documents, which are then imported into a relational database. Data mining is then implemented on the resultant dataset to produce a series of ranking positions for monophonic note patterns within the music based upon the relative frequencies of their appearances within specified time periods. Additionally, a similarity algorithm is used to investigate the possible ancestral relationships between different monophonic note patterns. Within the limitations of the working definitions and assumptions made in the research, it was shown that there is evidence for the evolutionary properties of selection, replication and variation, and the replicator properties of longevity, fecundity and copying fidelity for some monophonic note patterns within the dataset

Music Encoding Conference Proceedings 2021. 19–22 July, 2021 University of Alicante (Spain): Onsite & Online. Edited by Stefan Münnich and David Rizo

Conference proceedings of the Music Encoding Conference 2021 with Foreword by Stefan Münnich and David Rizo