On Because and Why

2018 ◽  
Vol 6 (2) ◽  
pp. 1-17
Author(s):  
Martin J Wheatman
Keyword(s):  
Language Processing ◽  
Test Suite ◽  
Text To Speech ◽  
Verbal Reasoning ◽  
The Third ◽  
Novel Approach

Because, as an act of verbal reasoning, is described in terms of its transitivity, composite assertions and reasoning. The latter includes induction through X because Y and the deduction subsequently afforded by why X. Once the component assertions X and Y are disavowed, it illustrates the third level of Peircean reasoning, abduction. The language engine, Enguage, is introduced and positioned as a novel approach to language processing. Three utterance repertoires of the Enguage test suite, which support because and why, are described. These are then applied using Enguage, and the resultant output is presented. A user can thus demonstrate reasoning interactively, via text-to-speech software, with a machine that can be said to understand why.

scholarly journals Automated Confirmation of Protein Annotation Using NLP and the UniProtKB Database

2020 ◽  
Vol 11 (1) ◽  
pp. 24
Author(s):  
Jin Tao ◽  
Kelly Brayton ◽  
Shira Broschat
Keyword(s):  
Language Processing ◽  
Fine Tuning ◽  
Support Vector ◽  
Protein Annotation ◽  
Computing Power ◽  
Journal Publication ◽  
Novel Approach ◽  
Uniprotkb Database ◽  
Public Repositories ◽  
Annotation Errors

Advances in genome sequencing technology and computing power have brought about the explosive growth of sequenced genomes in public repositories with a concomitant increase in annotation errors. Many protein sequences are annotated using computational analysis rather than experimental verification, leading to inaccuracies in annotation. Confirmation of existing protein annotations is urgently needed before misannotation becomes even more prevalent due to error propagation. In this work we present a novel approach for automatically confirming the existence of manually curated information with experimental evidence of protein annotation. Our ensemble learning method uses a combination of recurrent convolutional neural network, logistic regression, and support vector machine models. Natural language processing in the form of word embeddings is used with journal publication titles retrieved from the UniProtKB database. Importantly, we use recall as our most significant metric to ensure the maximum number of verifications possible; results are reported to a human curator for confirmation. Our ensemble model achieves 91.25% recall, 71.26% accuracy, 65.19% precision, and an F1 score of 76.05% and outperforms the Bidirectional Encoder Representations from Transformers for Biomedical Text Mining (BioBERT) model with fine-tuning using the same data.

scholarly journals Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bo Sun ◽  
Fei Zhang ◽  
Jing Li ◽  
Yicheng Yang ◽  
Xiaolin Diao ◽  
...  
Keyword(s):  
Information Sharing ◽  
Language Processing ◽  
Medical Information ◽  
Medical Professional ◽  
Semantic Interoperability ◽  
Medical Information System ◽  
Search Term ◽  
Search Terms ◽  
Novel Approach ◽  
Test Sets

Abstract Background With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can improve semantic interoperability. One key improvement of openEHR is that it allows for the use of existing archetypes. The crucial problem is how to improve the precision and resolve ambiguity in the archetype retrieval. Method Based on the query expansion technology and Word2Vec model in Nature Language Processing (NLP), we propose to find synonyms as substitutes for original search terms in archetype retrieval. Test sets in different medical professional level are used to verify the feasibility. Result Applying the approach to each original search term (n = 120) in test sets, a total of 69,348 substitutes were constructed. Precision at 5 (P@5) was improved by 0.767, on average. For the best result, the P@5 was up to 0.975. Conclusions We introduce a novel approach that using NLP technology and corpus to find synonyms as substitutes for original search terms. Compared to simply mapping the element contained in openEHR to an external dictionary, this approach could greatly improve precision and resolve ambiguity in retrieval tasks. This is helpful to promote the application of openEHR and advance EHR information sharing.

scholarly journals Prebiotics: A Novel Approach to Treat Hepatocellular Carcinoma

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Naz Fatima ◽  
Tasleem Akhtar ◽  
Nadeem Sheikh
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Antitumor Effect ◽  
Gut Permeability ◽  
Gut Flora ◽  
Effective Barrier ◽  
The Third ◽  
Oncogenic Pathways ◽  
Novel Approach ◽  
Genetic Modifications

Hepatocellular carcinoma is one of the fatal malignancies and is considered as the third leading cause of death. Mutations, genetic modifications, dietary aflatoxins, or impairments in the regulation of oncogenic pathways may bring about liver cancer. An effective barrier against hepatotoxins is offered by gut-liver axis as a change in gut permeability and expanded translocation of lipopolysaccharides triggers the activation of Toll-like receptors which stimulate the process of hepatocarcinogenesis. Prebiotics, nondigestible oligosaccharides, have a pivotal role to play when it comes to inducing an antitumor effect. A healthy gut flora balance is imperative to downregulation of inflammatory cytokines and reducing lipopolysaccharides induced endotoxemia, thus inducing the antitumor effect.

scholarly journals Production of germ-free mosquitoes via transient colonisation allows stage-specific investigation of host-microbiota interactions

2019 ◽  
Author(s):  
Ottavia Romoli ◽  
Johan Claes Schönbeck ◽  
Siegfried Hapfelmeier ◽  
Mathilde Gendrin
Keyword(s):  
Larval Development ◽  
Emerging Adults ◽  
Larval Instar ◽  
Bacterial Colonisation ◽  
Germ Free ◽  
Functional Studies ◽  
The Third ◽  
Novel Approach ◽  
Folate Biosynthesis ◽  
Vector Borne

AbstractThe mosquito microbiota impacts the physiology of its host and is essential for normal larval development, thereby influencing transmission of vector-borne pathogens. Germ-free mosquitoes generated with current methods show larval stunting and developmental deficits. Therefore, functional studies of the mosquito microbiota have so far mostly been limited to antibiotic treatments of emerging adults. In this study, we developed a novel approach to produce germ-free Aedes aegypti mosquitoes. It is based on reversible colonisation with bacteria genetically modified to allow complete decolonisation at any developmental stage. We show that, unlike germ-free mosquitoes previously produced using sterile diets, reversibly colonised mosquitoes show no developmental retardation and reach the same size as control adults. This allowed us to uncouple the study of the microbiota in larvae and adults. In adults, we detected no impact of bacterial colonisation on mosquito fecundity or longevity. In larvae, we performed a transcriptome analysis and diet supplementation experiments following decolonisation during the third larval instar. Our data suggest that bacteria support larval development by contributing to folate biosynthesis and by enhancing energy storage. Our study establishes a novel tool to study the microbiota in insects and deepens our knowledge on the metabolic contribution of bacteria to mosquito development.

Using Big Data Opinion Mining to Predict Rises and Falls in the Stock Price Index

2015 ◽  
pp. 30-42
Author(s):  
Yoosin Kim ◽  
Michelle Jeong ◽  
Seung Ryul Jeong
Keyword(s):  
Big Data ◽  
Language Processing ◽  
Stock Price ◽  
Opinion Mining ◽  
Predictive Accuracy ◽  
Online News ◽  
Social Phenomena ◽  
Price Increases ◽  
Novel Approach ◽  
Investment Decision Making

In light of recent research that has begun to examine the link between textual “big data” and social phenomena such as stock price increases, this chapter takes a novel approach to treating news as big data by proposing the intelligent investment decision-making support model based on opinion mining. In an initial prototype experiment, the researchers first built a stock domain-specific sentiment dictionary via natural language processing of online news articles and calculated sentiment scores for the opinions extracted from those stories. In a separate main experiment, the researchers gathered 78,216 online news articles from two different media sources to not only make predictions of actual stock price increases but also to compare the predictive accuracy of articles from different media sources. The study found that opinions that are extracted from the news and treated with proper sentiment analysis can be effective in predicting changes in the stock market.

A NOVEL APPROACH FOR SEMANTIC WEB APPLICATION IN ONLINE EDUCATION BASED ON STEGANOGRAPHY

2022 ◽  
Vol 17 (4) ◽  
pp. 0-0
Keyword(s):  
Online Education ◽  
Semantic Web ◽  
Web 2.0 ◽  
Language Processing ◽  
Web Application ◽  
Information Needs ◽  
Extensive Literature ◽  
Web 3.0 ◽  
Novel Approach ◽  
Current Concerns

Semantic Web technology is not new as most of us contemplate; it has evolved over the years. Linked Data web terminology is the name set recently to the Semantic Web. Semantic Web is a continuation of Web 2.0 and it is to replace existing technologies. It is built on Natural Language processing and provides solutions to most of the prevailing issues. Web 3.0 is the version of Semantic Web caters to the information needs of half of the population on earth. This paper links two important current concerns, the security of information and enforced online education due to COVID-19 with Semantic Web. The Steganography requirement for the Semantic web is discussed elaborately, even though encryption is applied which is inadequate in providing protection. Web 2.0 issues concerning online education and semantic Web solutions have been discussed. An extensive literature survey has been conducted related to the architecture of Web 3.0, detailed history of online education, and Security architecture. Finally, Semantic Web is here to stay and data hiding along with encryption makes it robust.

Mining Domain Terminologies Using Search Engine's Query Log

2021 ◽  
Vol 20 (6) ◽  
pp. 1-32
Author(s):  
Weijian Ni ◽  
Tong Liu ◽  
Qingtian Zeng ◽  
Nengfu Xie
Keyword(s):  
Language Processing ◽  
Heterogeneous Network ◽  
Transductive Learning ◽  
Query Log ◽  
Domain Specific ◽  
Novel Approach ◽  
Commercial Search Engine ◽  
Domain Expertise ◽  
Traditional Approaches ◽  
Domain Independent

Domain terminologies are a basic resource for various natural language processing tasks. To automatically discover terminologies for a domain of interest, most traditional approaches mostly rely on a domain-specific corpus given in advance; thus, the performance of traditional approaches can only be guaranteed when collecting a high-quality domain-specific corpus, which requires extensive human involvement and domain expertise. In this article, we propose a novel approach that is capable of automatically mining domain terminologies using search engine's query log—a type of domain-independent corpus of higher availability, coverage, and timeliness than a manually collected domain-specific corpus. In particular, we represent query log as a heterogeneous network and formulate the task of mining domain terminology as transductive learning on the heterogeneous network. In the proposed approach, the manifold structure of domain-specificity inherent in query log is captured by using a novel network embedding algorithm and further exploited to reduce the need for the manual annotation efforts for domain terminology classification. We select Agriculture and Healthcare as the target domains and experiment using a real query log from a commercial search engine. Experimental results show that the proposed approach outperforms several state-of-the-art approaches.

Creation of annotated country-level dialectal Arabic resources: An unsupervised approach

2021 ◽  
pp. 1-42
Author(s):  
Maha J. Althobaiti
Keyword(s):  
Language Processing ◽  
Social Networking Sites ◽  
Linguistic Diversity ◽  
Poor Performance ◽  
Country Level ◽  
Part Of Speech ◽  
Novel Approach ◽  
Agreement Score ◽  
Arabic Dialects ◽  
Dialectal Arabic

Abstract The wide usage of multiple spoken Arabic dialects on social networking sites stimulates increasing interest in Natural Language Processing (NLP) for dialectal Arabic (DA). Arabic dialects represent true linguistic diversity and differ from modern standard Arabic (MSA). In fact, the complexity and variety of these dialects make it insufficient to build one NLP system that is suitable for all of them. In comparison with MSA, the available datasets for various dialects are generally limited in terms of size, genre and scope. In this article, we present a novel approach that automatically develops an annotated country-level dialectal Arabic corpus and builds lists of words that encompass 15 Arabic dialects. The algorithm uses an iterative procedure consisting of two main components: automatic creation of lists for dialectal words and automatic creation of annotated Arabic dialect identification corpus. To our knowledge, our study is the first of its kind to examine and analyse the poor performance of the MSA part-of-speech tagger on dialectal Arabic contents and to exploit that in order to extract the dialectal words. The pointwise mutual information association measure and the geographical frequency of word occurrence online are used to classify dialectal words. The annotated dialectal Arabic corpus (Twt15DA), built using our algorithm, is collected from Twitter and consists of 311,785 tweets containing 3,858,459 words in total. We randomly selected a sample of 75 tweets per country, 1125 tweets in total, and conducted a manual dialect identification task by native speakers. The results show an average inter-annotator agreement score equal to 64%, which reflects satisfactory agreement considering the overlapping features of the 15 Arabic dialects.

Knowing ‘who she is’ based on ‘where she is’: The effect of co-speech gesture on pronoun comprehension

2012 ◽  
Vol 4 (2) ◽  
pp. 75-98 ◽  
Author(s):  
Whitney Goodrich Smith ◽  
Carla L. Hudson Kam
Keyword(s):  
Language Processing ◽  
The Third ◽  
The Way

AbstractWe examine whether pronoun interpretation is affected by naturalistic co-speech gesture. Participants in three conditions watched narrations containing ambiguous pronouns. In one condition the narrator produced gestures consistent with order-of-mention; in another, they conflicted with order-of-mention; and in the third, she did not gesture. Results showed that when the gestures conflicted with order-of-mention participants were much less likely to interpret the pronoun as referring to the first-mentioned character. In a second experiment we ruled out the possibility that participants were simply picking up on differences within the speech itself. These results extend previous work on gesture and language processing by showing that the information in gesture can influence the way people interpret words which by their nature are ambiguous, and that this influence is similar to that of well-known speech internal cues.

Research Design in Team-Based Qualitative Research

2018 ◽  
Author(s):  
Judith Davidson
Keyword(s):  
Qualitative Research ◽  
Research Design ◽  
Team Formation ◽  
Digital Tools ◽  
Project Organization ◽  
Data Archiving ◽  
Project Management System ◽  
The Third ◽  
Novel Approach ◽  
Start Up

In the introduction to this chapter and interwoven throughout the text is the message that qualitative research begins and ends in writing, which in this case means that research design is a beginning point for that writing. This chapter is composed of three major sections that illustrate how team start-up is critical to how the writing will proceed down the line. The first section—Team Formation—provides detailed information on issues to consider in establishing the team in a manner that will be most beneficial to the conduct of qualitative research. The second section—Research Design and Project Organization—discusses early writing tasks, establishing a project management system, and the importance of linking all of this to a data archiving plan. Digital tools are discussed in some depth. The third section—Caring: Internalized and Externalized—suggests a novel approach to the issue of ethics and team management.

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