Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review

Over the last couple of decades, community question-answering sites (CQAs) have been a topic of much academic interest. Scholars have often leveraged traditional machine learning (ML) and deep learning (DL) to explore the ever-growing volume of content that CQAs engender. To clarify the current state of the CQA literature that has used ML and DL, this paper reports a systematic literature review. The goal is to summarise and synthesise the major themes of CQA research related to (i) questions, (ii) answers and (iii) users. The final review included 133 articles. Dominant research themes include question quality, answer quality, and expert identification. In terms of dataset, some of the most widely studied platforms include Yahoo! Answers, Stack Exchange and Stack Overflow. The scope of most articles was confined to just one platform with few cross-platform investigations. Articles with ML outnumber those with DL. Nonetheless, the use of DL in CQA research is on an upward trajectory. A number of research directions are proposed

Ranking online consumer reviews

YesProduct reviews are posted online by the hundreds and thousands for popular products. Handling such a large volume of continuously generated online content is a challenging task for buyers, sellers and researchers. The purpose of this study is to rank the overwhelming number of reviews using their predicted helpfulness scores. The helpfulness score is predicted using features extracted from review text, product description, and customer question-answer data of a product using the random-forest classifier and gradient boosting regressor. The system classifies reviews into low or high quality with the random-forest classifier. The helpfulness scores of the high-quality reviews are only predicted using the gradient boosting regressor. The helpfulness scores of the low-quality reviews are not calculated because they are never going to be in the top k reviews. They are just added at the end of the review list to the review-listing website. The proposed system provides fair review placement on review listing pages and makes all high-quality reviews visible to customers on the top. The experimental results on data from two popular Indian e-commerce websites validate our claim, as 3–4 newer high-quality reviews are placed in the top ten reviews along with 5–6 older reviews based on review helpfulness. Our findings indicate that inclusion of features from product description data and customer question-answer data improves the prediction accuracy of the helpfulness score.Ministry of Electronics and Information Technology (MeitY), Government of India for financial support during research work through “Visvesvaraya PhD Scheme for Electronics and IT”

Safe infant feeding in healthcare facilities: Assessment of infection prevention and control conditions and behaviors in India, Malawi, and Tanzania

Infants need to receive care in environments that limit their exposure to pathogens. Inadequate water, sanitation, and hygiene (WASH) environments and suboptimal infection prevention and control practices in healthcare settings contribute to the burden of healthcare-associated infections, which are particularly high in low-income settings. Specific research is needed to understand infant feeding preparation in healthcare settings, a task involving multiple behaviors that can introduce pathogens and negatively impact health. To understand feeding preparation practices and potential risks, and to inform strategies for improvement, we assessed facility WASH environments and observed infant feeding preparation practices across 12 facilities in India, Malawi, and Tanzania serving newborn infants. Research was embedded within the Low Birthweight Infant Feeding Exploration (LIFE) observational cohort study, which documented feeding practices and growth patterns to inform feeding interventions. We assessed WASH-related environments and feeding policies of all 12 facilities involved in the LIFE study. Additionally, we used a guidance-informed tool to carry out 27 feeding preparation observations across 9 facilities, enabling assessment of 270 total behaviors. All facilities had ‘improved’ water and sanitation services. Only 50% had written procedures for preparing expressed breastmilk; 50% had written procedures for cleaning, drying, and storage of infant feeding implements; and 33% had written procedures for preparing infant formula. Among 270 behaviors assessed across the 27 feeding preparation observations, 46 (17.0%) practices were carried out sub-optimally, including preparers not handwashing prior to preparation, and cleaning, drying, and storing of feeding implements in ways that do not effectively prevent contamination. While further research is needed to improve assessment tools and to identify specific microbial risks of the suboptimal behaviors identified, the evidence generated is sufficient to justify investment in developing guidance and programing to strengthen infant feeding preparation practices to ensure optimal newborn health

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Actinic keratosis in vitiligo after oral PUVAsol therapy with review

Abstract Vitiligo is an acquired disorder characterised by depigmentation. The etiopathogenesis is still unclear and many theories have been proposed for the same. It is believed that due to lack of protective melanin, a vitiliginous patch is more prone to photodamage by UV radiation and development of skin cancers especially following PUVASOL therapy. But, few cutaneous malignancies have been reported and even fewer cases of actinic keratoses have been reported over a vitiliginous skin. Here, we report a case of elderly female who developed actinic keratoses over longstanding sun exposed vitiliginous skin post PUVA therapy

Sequential Purchase Recommendation System for E-Commerce Sites

Part 4: Engineering of Enterprise Software ProductsInternational audienceTo find out which product should be recommended to the customer and when to recommend is done by the recommender system. Different approaches by using customer profile and product description are used to build recommender system. Although these information are not enough to recommend, sometimes buying of some products occurs in a stepwise manner, where buying of one product follows the buying of other products. The purpose of this research is to find the sequences followed by customers while purchasing products to improve the efficiency of recommender system. Sequence pattern mining is used to find out the order of purchasing products. The duration we find tells the time gap between the purchased product and recommendation of next sequential products

Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum $p_\mathrm{T}$ and rapidity $y$. The measurement is performed using proton-proton collision data at $\sqrt{s}$ = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb$^{-1}$. The jets are reconstructed with the anti-$k_\mathrm{T}$ algorithm using a distance parameter of $R$ = 0.4, within the rapidity interval $\lvert y\rvert$$\lt$ 2, and across the kinematic range 0.06 $\lt$$p_\mathrm{T}$$\lt$ 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling $\alpha_\mathrm{S}$

Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum $p_\mathrm{T}$ and rapidity $y$. The measurement is performed using proton-proton collision data at $\sqrt{s}$ = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb$^{-1}$. The jets are reconstructed with the anti-$k_\mathrm{T}$ algorithm using a distance parameter of $R$ = 0.4, within the rapidity interval $\lvert y\rvert$$\lt$ 2, and across the kinematic range 0.06 $\lt$$p_\mathrm{T}$$\lt$ 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling $\alpha_\mathrm{S}$