Rapid Classification and Analysis for E-Commerce Goods Based on Multitask Learning

Today’s E-commerce is hot, while the categorization of goods cannot be handled better, especially to achieve the demand of multiple tasks. In this paper, we propose a multitask learning model based on a CNN in parallel with a BiLSTM optimized by an attention mechanism as a training network for E-commerce. The results showed that the fast classification task of E-commerce was performed using only 10% of the total number of products. The experimental results show that the accuracy of w-item2vec for product classification can be close to 50% with only 10% of the training data. Both models significantly outperform other models in terms of classification accuracy.

Advertising with scarcity messages and attitudes for luxury skin-care products

PurposeA number of types of scarcity messages are often used in Internet advertisements, but all these types have not been directly compared to each other.Design/methodology/approachCollege students (n = 789) were surveyed about five advertising choices for luxury skin-care products consisting of scarcity messages of high-demand, low-stock, limited-time, countdown timer and regular advertising without any scarcity message. Outcomes were product classification attitudes of functional and symbolic and psychological attitudes of persuasion knowledge and advertising skepticism.FindingsThe study found that high-demand message had greater functional attitudes and greater symbolic attitudes than regular advertising. Limited-time message had greater symbolic attitudes than regular advertising. High-demand message had lower advertising skepticism attitudes than regular advertising.Practical implicationsThe authors recommend that when a luxury skin-care product is in high demand, that marketers should use high-demand messages in their advertising. Marketers of luxury skin-care products may also benefit from using limited-time message advertisements.Originality/valueThis is the first study to directly compare the scarcity message advertising types of high-demand, low-stock, limited-time, countdown timer with regular advertising without any scarcity message.

Elements of digitalization in organization of traceability of poultry processing products

The paper provides data on the systematization of poultry processing products, highlighting the basic and specific principles of assigning products to homogeneous species and groups. The performed analysis made it possible to assign a digital or letter designation to each product classification feature. In the course of the research, the order of presentation of information about the properties of products was determined when compiling the name of the product, as well as in the composition of the alphanumeric code. Schemes for drawing up alphanumeric codes for general food products – slaughter products and processed products of poultry slaughter products – have been developed and presented.

The Search for Putative Hits in Combating Leishmaniasis: The Contributions of Natural Products Over the Last Decade

Despite advancements in the areas of omics and chemoinformatics, potent novel biotherapeutic molecules with new modes of actions are needed for leishmaniasis. The socioeconomic burden of leishmaniasis remains alarming in endemic regions. Currently, reports from existing endemic areas such as Nepal, Iran, Brazil, India, Sudan and Afghanistan, as well as newly affected countries such as Peru, Bolivia and Somalia indicate concerns of chemoresistance to the classical antimonial treatment. As a result, effective antileishmanial agents which are safe and affordable are urgently needed. Natural products from both flora and fauna have contributed immensely to chemotherapeutics and serve as vital sources of new chemical agents. This review focuses on a systematic cross-sectional view of all characterized anti-leishmanial compounds from natural sources over the last decade. Furthermore, IC50/EC50, cytotoxicity and suggested mechanisms of action of some of these natural products are provided. The natural product classification includes alkaloids, terpenes, terpenoids, and phenolics. The plethora of reported mechanisms involve calcium channel inhibition, immunomodulation and apoptosis. Making available enriched data pertaining to bioactivity and mechanisms of natural products complement current efforts geared towards unraveling potent leishmanicides of therapeutic relevance. Graphic Abstract

Developing Data-Conscious Deep Learning Models for Product Classification

In online commerce systems that trade in many products, it is important to classify the products accurately according to the product description. As may be expected, the recent advances in deep learning technologies have been applied to automatic product classification. The efficiency of a deep learning model depends on the training data and the appropriateness of the learning model for the data domain. This is also applicable to deep learning models for automatic product classification. In this study, we propose deep learning models that are conscious of input data comprising text-based product information. Our approaches exploit two well-known deep learning models and integrate them with the processes of input data selection, transformation, and filtering. We demonstrate the practicality of these models through experiments using actual product information data. The experimental results show that the models that systematically consider the input data may differ in accuracy by approximately 30% from those that do not. This study indicates that input data should be sufficiently considered in the development of deep learning models for product classification.

Penerapan Data Mining untuk Klasifikasi Produk Merk Bata Menggunakan Algoritma K-Means

Tanjungbalai Bata Store is a store that is engaged in the business of selling products and every day processes purchase data, sales data and transaction data. Transaction data is the result of sales that can be obtained so that store management knows the strategies that will be carried out to increase sales results. As for consumers who make transactions at stores for a separate reason, especially because of the completeness and many models that can be obtained from the Tanjungbalai brick shop, another reason is that the Tanjungbalai Brick Shop can provide a sense of comfort and peace in addition and the cleanliness seen from the store . There are many types of products sold at the Tanjungbalai Brick Shop. However, Tanjungbalai Brick Shop cannot classify products that are selling well and those that are not selling well. So that the difficulties experienced are the frequent shortage of stock of products that sell well because sales are high and the accumulation of products that are not selling well in the warehouse because the sellers are low. Based on the problems above, data mining is needed to classify which products are in demand and which are not. Data mining and k-means methods can help in this research combined with the PHP programming language and MySQL database. Keywords:Data Mining; Product Classification; K-Means Algorithm. Abstrak:Toko Bata Tanjungbalai adalah toko yang bergerak di bidang bisnis penjulalan produk dan setiap harinya melalukan proses data pembelian, data penjualan maupun data transaksi. Data transaksi merupakan hasil penjualan yang di dapat agar manajemen toko mengetahui strategi yang akan di lakukan untuk meningkatkan hasil penjualan. Adapun konsumen yang melakukan transaksi di toko memiliki alas an tersendiri ataupun di karenakan kelengkapan dan banyak model yang bisa di dapatkan dari toko bata tanjungbalai, alasan yang lain adalah Toko Bata Tanjungbalai dapat memberikan rasa nyamandan tentram di tambah lagi keramahan dan kebersihan yang di lihat dari toko tersebut. Ada banyak jenis produk yang terjual di Toko Bata Tanjungbalai, namun toko bata Tanjungbalai tidaklah mampu dalam membagikan kelompok produk tersebut masuk kategori laris dan tidak laris. Sehingga kesulitan yang dialami yaitu seringnya kekurangan stok produk yang laku karena penjualannya tinggi dan menumpuknya produk yang tidak laris di gudang karena penjualnnya rendah. Berdasarkan permasalahan di atas maka dibutuhkan data mining untuk mengelompokkan produk mana saja yang laris dan tidak. Data mining dan metode k-meansdapat membantu dalam penelitian ini dipadukan dengan pemrograman PHP dan MySQL. Kata Kunci :Data Mining; Klasifikasi Produk; Algoritma K-Means.