Indexing Vocabulary Research Articles

Passport: Improving Automated Formal Verification Using Identifiers

Formally verifying system properties is one of the most effective ways of improving system quality, but its high manual effort requirements often render it prohibitively expensive. Tools that automate formal verification by learning from proof corpora to synthesize proofs have just begun to show their promise. These tools are effective because of the richness of the data the proof corpora contain. This richness comes from the stylistic conventions followed by communities of proof developers, together with the powerful logical systems beneath proof assistants. However, this richness remains underexploited, with most work thus far focusing on architecture rather than on how to make the most of the proof data. This article systematically explores how to most effectively exploit one aspect of that proof data: identifiers.We develop the Passport approach, a method for enriching the predictive Coq model used by an existing proof-synthesis tool with three new encoding mechanisms for identifiers: category vocabulary indexing, subword sequence modeling, and path elaboration. We evaluate our approach’s enrichment effect on three existing base tools: ASTactic, Tac, and Tok. In head-to-head comparisons, Passport automatically proves 29% more theorems than the best-performing of these base tools. Combining the three tools enhanced by the Passport approach automatically proves 38% more theorems than combining the three base tools. Finally, together, these base tools and their enhanced versions prove 45% more theorems than the combined base tools. Overall, our findings suggest that modeling identifiers can play a significant role in improving proof synthesis, leading to higher-quality software.

Methods for Assessing the Psychological Tension of Social Network Users during the Coronavirus Pandemic and Its Uses for Predictive Analysis

This article address approaches to the development of methods for assessing the psychological state of social network members during the coronavirus pandemic through sentiment analysis of messages. The purpose of the work is to determine the psychological tension index by using a previously developed thematically ranked dictionary. Researchers have investigated methods to evaluate psychological tension among social network users and to forecast the psychological distress. The approach is novel in the sense that it ranks emojis by mood, considering both the emotional tone of tweets and the emoji’s dictionary meanings. A novel method is proposed to assess the dynamics of the psychological state of social network users as an indicator of their subjective well-being, and develop targeted interventions for help. Based on the ranking of the Emotional Vocabulary Index (EVI) and Subjective Well-being Index (SWI), a scheme is developed to predict the development of psychological tension. The significance lies in the efficient assessment of the fluctuations in the mental wellness of network users as an indication of their emotions and a prerequisite for further predictive analysis. The findings gave a computed value of EVI of 306.15 for April 2022. The prediction accuracy of 88.75% was achieved.

Vocabulary Index as a Sustainable Resource for Teaching Extended Writing in the Post-Pandemic Era

In the wake of the COVID-19 pandemic, Malaysian English teachers identified a pressing need to support upper primary school pupils, particularly those in the upper levels, in the effective composition of extended writing. Additionally, these educators required more innovative methodologies for teaching vocabulary in this context. Consequently, the current study aimed to develop a vocabulary index as a suggested resource for Malaysian English teachers instructing upper primary school pupils on extended writing. To achieve this, a quantitative computational research strategy and corpus-driven research design were employed. A purposive sampling technique was used to select 560 advanced upper primary school pupils from 28 schools, each with high English performance in the capital of each state and the federal territory of Malaysia, who produced a total of 152,187 words in extended writing for analysis. LancsBox, a primary computational linguistics application, was used for data processing. Given that the vocabulary index for extended writing necessitates a more comprehensive coverage of vocabulary, functional and content words were included, and keywords, raw and normalised frequencies were analysed and reported. Through the vocabulary index built in this study, the researchers found English teachers in Malaysia should utilise local issues in writing prompts, emphasise the use of both positive and negative adjectives, introduce complex sentence structures to enhance pupils’ writing abilities and also train pupils to organise the ideas in their writing. Future linguistic studies could replicate the present investigation, so that it can respond to their classroom needs.

The mutability of fiction descriptors: the evolution of ‘pulp’

The term ‘pulp’ is rarely used in library cataloguing as a descriptor for fiction and does not appear in indexing vocabularies such as the Library of Congress Genre/Form Terms (LCGFT). In contrast, it is used extensively as a tag for large numbers of fiction titles in social cataloguing sites such as LibraryThing and Goodreads. We explore the reasons for the library world’s reluctance to adopt the term, with reference to the history of the term and the fiction it represents. We then report on a comparative thematic analysis of LibraryThing user reviews of ‘old’ and ‘new’ pulp, uncovering an evolution in the way the term has been used. Its more positive usage in contemporary descriptions suggests that pulp’s exclusion from LCGFT should be reviewed.

Deep learning based high similarity automatic retrieval algorithm for vocabulary interpretation of workers of Food Sector in china

In order to build a high similarity English vocabulary interpretation domain knowledge base and ensure the automatic retrieval effect of high similarity English vocabulary interpretation, this paper standardizes the automatic retrieval specification of authoritative interpretation of high similarity English vocabulary knowledge, and takes high similarity English vocabulary as the source corpus of the knowledge base. On the basis of the existing work, this paper attempts to propose an automatic retrieval algorithm of high similarity English word interpretation based on deep learning. The goal is to diversify the sources of high similarity English word knowledge and achieve the accuracy of automatic retrieval of word interpretation while ensuring a certain knowledge coverage. A suitable domain knowledge base of machine-readable dictionary is constructed through a new method It can not only provide accurate knowledge information for high similarity English vocabulary, but also provide retrieval verification for user needs analysis and high similarity English vocabulary indexing of snippet. The experimental results show that the algorithm based on deep learning is effective and can fully meet the research requirements.

Analysis of AI MT Based on Fuzzy Algorithm

The advancement of artificial intelligence technology is highly dependent on advancements in computer technology. The former created the technology for the latter. In the near future, we believe computer artificial intelligence technology will be further developed and better serve people. In other words, the data or note producer will edit the bridge segments with prominent contradictions in each program and broadcast them through the network with the titles that people are interested in, which has gotten a lot of attention and comments. This paper investigates a new fuzzy evaluation model by starting with the current situation. This paper investigates fuzzy algorithm-based artificial intelligence machine translation. The order of machine translation follows the trend in the figure, whereas the distribution of HEMTM machine translation is more concentrated under the HEMTM model. The average reliability ratio of the data mining algorithm is 0.97, the average reliability ratio of the decision tree algorithm is 0.84, the average reliability ratio of the machine learning algorithm is 0.71, and the average reliability ratio of the fuzzy algorithm is 1.34 when the vocabulary index is 15. The proportion of fuzzy algorithms in this paper is the highest of the four algorithms. It can be transformed into the contraction of frequency-domain coefficients in artificial intelligence machine translation using a fuzzy algorithm, greatly simplifying the operation. However, it will cause the ringing effect of fuzzy algorithm boundary in machine translation because it cannot well express the singular information of signals such as boundary. The extent of this effect is determined by the artificial intelligence machine translation breadth.

Toponymic Legends of Ural Amateur Miners

This article analyses the legends of Ural amateur miners (gorshchiks) — people who recover precious stones and gemstones as their private business. The folklore of amateur miners still remains virtually unstudied; that differentiates it from the folklore of professional miners (gorniaks). The research is based on field records of various periods, both published and unpublished. These records are part of the card index Vocabulary, Toponymy, Ethnography of the Stone kept at the Department of the Russian Language, General Linguistics and Verbal Communication (Ural Federal University). The article demonstrates that the legends spring from the real working practices of amateur miners; traditional motifs, including fantastic ones, add to these legends. The research centres on toponymic legends which are considered as a source for deriving the inner form and motivation of the place name (toponym). The author points out that applying to historical records and a comprehensive ethnolinguistic analysis help establish if the motivation of the toponym given in the legend is correct or erroneous. The research reveals that a correlation between a firmly established legendary motif and a firmly established nominative model helps correctly determine the motivation of a toponym. In addition, the amateur miners’ legends are seen as a source for studying their way of life and worldview. The article analyses the following motifs characteristic of the amateur miners’ legends: the stroke of luck and the chance discovery of gemstones, the not given treasure and the unlucky development of a mine, the prophetic dream, the violation of a taboo and punishment for greed, the miraculous richness of mines. The author highlights specific professional interpretations that well-known folklore motifs acquire in the amateur miners’ legends. Specifically, the self-burial of the Chud people is replaced by the motif of treasure burial.

Repercussion of the implementation of the Picture Exchange Communication System - PECS in the overload index of mothers of children with Autism Spectrum Disorder.

The aim of this study was to analyze the repercussion of the implementation of PECS on the burden index of mothers of children with Autism Spectrum Disorder (ASD). This was a longitudinal study (CEP 0403/2017). The sample consisted of 20 mother and child with ASD. The mothers were on average 41 years and 5 months and the children were 7 years and 2 months old. Fifteen children were male and five were female. The brazilian version of the Burden Interview scale was applied to verify the level of caregiver burden. The Autism Behavior Checklist (ABC) was applied to the analysis of non-adaptive behaviors and to analyze the lexical repertoire: Auditory and Expressive Vocabulary Tests. The PECS Implementation Program was composed of 24 sessions of individual speech therapy with the active presence of mothers. At the end all children and mothers were reevaluated with part of the instruments. There was a tendency to reduce maternal overload indexes after the implementation of the PECS. There was a significant decrease in non-adaptive behaviors and an increase in the expressive and auditory vocabulary indexes of the children at the final moment of the study. We did not observe a significant correlation between the degrees of overload with age, schooling and intellectual quotient of children, nor schooling and maternal socioeconomic status. It was possible to analyze the repercussion of the implementation of the PECS on the burden of mothers of children with ASD assisted by the Program.

Developing A Model for Predicting the Speech Intelligibility of South Korean Children with Cochlear Implantation using a Random Forest Algorithm

The random forest technique, a tree-based study model, predicts the results by using random decision trees based on the bootstrap technique. Therefore, it has a high prediction power and fewer errors, which are advantages of this method. This study aimed to provide baseline data regarding the language therapy after cochlear implantation by identifying the factors associated with the speech intelligibility of children with cochlear implantation. This study evaluating the factors associated with the articulation accuracy of children with cochlear implantation. This study targeted 82 hearing-impaired children, who lived in Seoul, Incheon, and Suwon areas, were between 4 and 8 years old, and had been worn cochlear implant at least one year and less than five years. Explanatory variables used in this study included gender, age, household income, the wear time of a cochlear implant, vocabulary index, and corrected hearing. Speech intelligibility was analyzed using the 'speech intelligibility test tool' composed of nine sentences. The predictive model for speech intelligibility of children with cochlear implants was developed using random forest. The major predictors of the articulation accuracy of children with cochlear implantation were the wear time of a cochlear implant, the time since cochlear implantation, vocabulary, household income, age, and gender, in the order of the magnitude. The final error rate of the random forest model developed by generating 500 bootstrap samples was 0.22, and the prediction rate was 78.8%. The results of this study on a prediction model suggested that it would be necessary to implement cochlear implantation and to develop a customized aural rehabilitation program considering the linguistic ability of a subject for enhancing the speech intelligibility of a child with cochlear implantation.

Relevansi Dan Penerapan Subject Authority dalam Sistem Temu Kembali Koleksi Kitab Kuning Pusat Perpustakaan UIN Maulana Malik Ibrahim Malang

This research describe about how relevation and subject authority implementation on yellow book collections in retrieval system UIN Maulana Malik Ibrahim Library Center Malang. Background in this research is from the past researchs and because UIN Maulana Malik Ibrahim Library Center Malang based from Islamic and have so many book collections. In this library have a different wisdom to managing book collections and general collections. Result from this research is : (1) relevansion rank yellow book collections in retrieval system UIN Maulana Malik Ibrahim Library Center Malang from subject authority method are low and not effective and ideal and then bring out recall 70% and precision 58.3%. (2) implementation process on subject authority yellow book collections UIN Maulana Malik Ibrahim Library Center Malang are not match with implementation principal, and have a result: there are not consistent using a subject (from 97 sample, 37 sample are not consistent), vocabulary index subject implementation don’t have a control language (from 97 sample, 56 are not controlling), using original name versus foreign is lack of attention (from 74 subject, there some Arabic name are not consistent with Arabic-Indonesian transliteration process) and subject authority implementation are not focus with primary books (in 16 book collections)

Pan-granularism and specificity

This article explores two important topics, granularity and specificity, and why they are important concepts for indexers. Fred Leise also offers a new term for the indexing vocabulary, ‘pan-granul...

Meshable: searching PubMed abstracts by utilizing MeSH and MeSH-derived topical terms.

Summary: Medical Subject Headings (MeSH®) is a controlled vocabulary for indexing and searching biomedical literature. MeSH terms and subheadings are organized in a hierarchical structure and are used to indicate the topics of an article. Biologists can use either MeSH terms as queries or the MeSH interface provided in PubMed® for searching PubMed abstracts. However, these are rarely used, and there is no convenient way to link standardized MeSH terms to user queries. Here, we introduce a web interface which allows users to enter queries to find MeSH terms closely related to the queries. Our method relies on co-occurrence of text words and MeSH terms to find keywords that are related to each MeSH term. A query is then matched with the keywords for MeSH terms, and candidate MeSH terms are ranked based on their relatedness to the query. The experimental results show that our method achieves the best performance among several term extraction approaches in terms of topic coherence. Moreover, the interface can be effectively used to find full names of abbreviations and to disambiguate user queries.Availability and Implementation: https://www.ncbi.nlm.nih.gov/IRET/MESHABLE/Contact: sun.kim@nih.govSupplementary information: Supplementary data are available at Bioinformatics online.

Knowledge Organisation and its Role in Multimedia Information Retrieval

KO KNOWLEDGE ORGANIZATION , Seite 180 - 183

Relação entre vocabulário receptivo e expressivo em crianças com transtorno específico do desenvolvimento da fala e da linguagem

OBJETIVO: comparar os índices de vocabulário receptivo e expressivo de crianças com Transtorno Específico do Desenvolvimento da Fala e da Linguagem. MÉTODOS: trata-se de estudo transversal, com amostra constituída por 21 crianças com Transtorno Específico do Desenvolvimento da Fala e da Linguagem, avaliadas em clínica-escola de Fonoaudiologia, sendo 9 crianças do gênero feminino e 12 crianças do gênero masculino, com idades entre 3 e 11 anos. Para este estudo foi utilizada a Prova de Vocabulário do Teste ABFW e o Teste de Vocabulário por Imagem Peabody - TVIP. RESULTADOS: 80,95% das crianças apresentaram desempenho adequado na avaliação do vocabulário expressivo, enquanto 52,4% apresentaram desempenho compatível com a faixa etária na avaliação do vocabulário receptivo. Não houve significância estatística. CONCLUSÃO: as crianças apresentaram melhor desempenho em avaliação do vocabulário expressivo em relação ao vocabulário receptivo. Esses dados comprovam a necessidade de um olhar atento e investigativo do fonoaudiólogo para os aspectos tanto de produção quanto de compreensão da linguagem.

Can Indexing Be Automated? The Example of the Deutsche Nationalbibliothek

The German Integrated Authority File (Gemeinsame Normdatei, GND), provides a broad controlled vocabulary for indexing documents on all subjects. Traditionally used for intellectual subject cataloging primarily for books, the Deutsche Nationalbibliothek (DNB, German National Library) has been working on developing and implementing procedures for automated assignment of subject headings for online publications. This project, its results, and problems are outlined in this article.

Task-Oriented Creative Writing with Système-D

The Système-D software package authored by Noblitt, Sola and Pet is a unique word processing program for creative writing in French. Geared toward elementary and intermediate level students, this program is designed to encourage students to write in French using a dictionary, a verb conjugator, a grammar index, a vocabulary index, and a phrase index. While confirming that Système-D provides challenging opportunities for autonomous expression in writing, this paper gives evidence from experience at Vanderbilt University that students are unlikely to use the features other than the dictionary. In order to profit from all that Système-D has to offer, this paper suggests a framework of task-oriented writing exercises built around meaningful situations which guide the students explicitly to exploit the important linguistic features easily accessible in the software. In addition, this paper discusses the importance of Système-D as it relates to evaluating written work and also its value with regard to the goals of proficiency-oriented instruction. Finally, this paper provides teachers with a comprehensive list of all the categories within the grammar, vocabulary and phrase indexes included in Système-D.

Learning to Distribute Vocabulary Indexing for Scalable Visual Search

In recent years, there is an ever-increasing research focus on Bag-of-Words based near duplicate visual search paradigm with inverted indexing. One fundamental yet unexploited challenge is how to maintain the large indexing structures within a single server subject to its memory constraint, which is extremely hard to scale up to millions or even billions of images. In this paper, we propose to parallelize the near duplicate visual search architecture to index millions of images over multiple servers, including the distribution of both visual vocabulary and the corresponding indexing structure. We optimize the distribution of vocabulary indexing from a machine learning perspective, which provides a “memory light” search paradigm that leverages the computational power across multiple servers to reduce the search latency. Especially, our solution addresses two essential issues: “What to distribute” and “How to distribute”. “What to distribute” is addressed by a “lossy” vocabulary Boosting, which discards both frequent and indiscriminating words prior to distribution. “How to distribute” is addressed by learning an optimal distribution function, which maximizes the uniformity of assigning the words of a given query to multiple servers. We validate the distributed vocabulary indexing scheme in a real world location search system over 10 million landmark images. Comparing to the state-of-the-art alternatives of single-server search <citerefgrp xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><citeref refid="ref5"/> </citerefgrp> , <citerefgrp xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><citeref refid="ref6"/></citerefgrp> , <citerefgrp xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <citeref refid="ref16"/></citerefgrp> and distributed search <citerefgrp xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <citeref refid="ref23"/></citerefgrp> , our scheme has yielded a significant gain of about 200% speedup at comparable precision by distributing only 5% words. We also report excellent robustness even when partial servers crash.

Automatic indexing by discipline and high-level categories: Methodology and potential applications.

This paper first describes the methodology of journal descriptor (JD) ndexing, based on human indexing at the journal level using only 127 descriptors, and applying statistical methods that associate this journal indexing with text words in a training set of MEDLINE® citations. These associations form the basis for automatic indexing of documents outside the training set. The paper then presents the new technique of semantic type (ST) indexing, based on JD indexing associated with each of 134 ST's, and applying the standard cosine coefficient measure to compare the similarity between the JD indexing of a document and the JD indexing of each ST. The ST indexing of the document is the list of ST's ranked in decreasing order of similarity between the JD indexing of the document and the JD indexing of the ST's. Discussion of the potential usefulness and application of the very general indexing provided by JD's and ST's comprises the remainder of the paper. JD's have been used for more than thirty years to search MEDLINE by discipline, and discipline-based indexing is in evidence on the Web. It is suggested, with several examples, that ST's may convey a unique slant of a document's content not normally represented in standard indexing vocabularies. Use of ST indexing to rank retrieved output is mentioned as a possible application. Notwithstanding the importance of methodology and performance issues, the intent of this paper is to explore questions of the potential utility and applicability of JD and ST indexing.

Controlled vocabularies and tags: An analysis of research methods

Social tagging has become increasingly common and is now often found in library catalogues or at least on library websites and blogs. Tags have been compared to controlled vocabulary indexing terms and have been suggested as replacements or enhancements for traditional indexing. This paper explored tagging and controlled vocabulary studies in the context of earlier studies examining title keywords, author keywords and user indexing and applied these results to a set of bibliographic records from PubMed which are also tagged on CiteULike. Preliminary results show that author and title keywords and tags are more similar to each other than to subject headings, though some user or author supplied terms do match subject headings exactly. Author keywords tend to be more specific than the other terms and could serve an additional distinguishing function when browsing.

Proof of concept

In this thesis we investigate the possibility to integrate domain-specific knowledge into biomedical information retrieval (IR). Recent decades have shown a fast growing interest in biomedical research, reflected by an exponential growth in scientific literature. An important problem for biomedical IR is dealing with the complex and inconsistent terminology encountered in biomedical publications. Dealing with the terminology problem requires domain knowledge stored in terminological resources: controlled indexing vocabularies and thesauri. The integration of this knowledge is, however, far from trivial. The first research theme investigates heuristics for obtaining word-based representations from biomedical text for robust retrieval. We investigated the effect of choices in document preprocessing heuristics on retrieval effectiveness. Document preprocessing heuristics such as stop word removal, stemming, and breakpoint identification and normalization were shown to strongly affect retrieval performance. An effective combination of heuristics was identified to obtain a word-based representation from text for the remainder of this thesis. The second research theme deals with concept-based retrieval. We compared a word-based to a concept-based representation and determined to what extent a manual concept-based representation can be automatically obtained from text. Retrieval based on only concepts was demonstrated to be significantly less effective than word-based retrieval. This deteriorated performance could be explained by errors in the classification process, limitations of the concept vocabularies and limited exhaustiveness of the concept-based document representations. Retrieval based on a combination of word-based and automatically obtained concept-based query representations did significantly improve word-only retrieval. In the third and last research theme we propose a cross-lingual framework for monolingual biomedical IR. In this framework, the integration of a concept-based representation is viewed as a cross-lingual matching problem involving a word-based and concept-based representation language. This framework gives us the opportunity to adopt a large set of established crosslingual information retrieval methods and techniques for this domain. Experiments with basic term-to-term translation models demonstrate that this approach can significantly improve word-based retrieval. Directions for future work are using these concepts for communication between user and retrieval system, extending upon the translation models and extending CLIR-enhanced concept-based retrieval outside the biomedical domain. Available online from http://purl.utwente.nl/publications/72481.