Dataset Information

The impact of semantics on aspect level opinion mining.

ABSTRACT: Recently, many users prefer online shopping to purchase items from the web. Shopping websites allow customers to submit comments and provide their feedback for the purchased products. Opinion mining and sentiment analysis are used to analyze products' comments to help sellers and purchasers decide to buy products or not. However, the nature of online comments affects the performance of the opinion mining process because they may contain negation words or unrelated aspects to the product. To address these problems, a semantic-based aspect level opinion mining (SALOM) model is proposed. The SALOM extracts the product aspects based on the semantic similarity and classifies the comments. The proposed model considers the negation words and other types of product aspects such as aspects' synonyms, hyponyms, and hypernyms to improve the accuracy of classification. Three different datasets are used to evaluate the proposed SALOM. The experimental results are promising in terms of Precision, Recall, and F-measure. The performance reaches 94.8% precision, 93% recall, and 92.6% f-measure.

SUBMITTER: Aboelela EM

PROVIDER: S-EPMC8237320 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The impact of semantics on aspect level opinion mining.

Aboelela Eman M EM Gad Walaa W Ismail Rasha R

PeerJ. Computer science 20210618

Recently, many users prefer online shopping to purchase items from the web. Shopping websites allow customers to submit comments and provide their feedback for the purchased products. Opinion mining and sentiment analysis are used to analyze products' comments to help sellers and purchasers decide to buy products or not. However, the nature of online comments affects the performance of the opinion mining process because they may contain negation words or unrelated aspects to the product. To addr ...[more]

PMID: 34239969

Similar Datasets

Project description:Following a request from the European Commission (EC), the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was asked to deliver a scientific opinion on the revision of the tolerable upper intake level (UL) for folic acid/folate. Systematic reviews of the literature were conducted to assess evidence on priority adverse health effects of excess intake of folate (including folic acid and the other authorised forms, (6S)-5-methyltetrahydrofolic acid glucosamine and l-5-methyltetrahydrofolic acid calcium salts), namely risk of cobalamin-dependent neuropathy, cognitive decline among people with low cobalamin status, and colorectal cancer and prostate cancer. The evidence is insufficient to conclude on a positive and causal relationship between the dietary intake of folate and impaired cognitive function, risk of colorectal and prostate cancer. The risk of progression of neurological symptoms in cobalamin-deficient patients is considered as the critical effect to establish an UL for folic acid. No new evidence has been published that could improve the characterisation of the dose-response between folic acid intake and resolution of megaloblastic anaemia in cobalamin-deficient individuals. The ULs for folic acid previously established by the Scientific Committee on Food are retained for all population groups, i.e. 1000 μg/day for adults, including pregnant and lactating women, 200 μg/day for children aged 1-3 years, 300 μg/day for 4-6 years, 400 μg/day for 7-10 years, 600 μg/day for 11-14 years and 800 μg/day for 15-17 years. A UL of 200 μg/day is established for infants aged 4-11 months. The ULs apply to the combined intake of folic acid, (6S)-5-methyltetrahydrofolic acid glucosamine and l-5-methyltetrahydrofolic acid calcium salts, under their authorised conditions of use. It is unlikely that the ULs for supplemental folate are exceeded in European populations, except for regular users of food supplements containing high doses of folic acid/5-methyl-tetrahydrofolic acid salts.

Dataset Information

The impact of semantics on aspect level opinion mining.

Publications

The impact of semantics on aspect level opinion mining.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets