scholarly journals Personalized Recommender System for Calculus using Content-Based Filtering Approach

2018 ◽  
Vol 7 (3.15) ◽  
pp. 110 ◽  
Author(s):  
Noor Latiffah Adam ◽  
Muhammad Alif Zulkafli ◽  
Shaharuddin Cik Soh ◽  
Nor Ashikin Mohamad Kamal ◽  
Nordin Abu Bakar
Keyword(s):  
Recommender System ◽  
The Internet ◽  
Internet Users ◽  
Basic Calculus ◽  
Personalized Recommender System ◽  
Many Sources ◽  
Content Based Filtering ◽  
Human Kind ◽  
The Web ◽  
Filtering Approach

In this millennial age, Internet is becoming essential to human kind. Along with the growth of Internet users, information is also becoming huge and starting to cause difficulties to find the relevant contents. Thus, the recommender system was introduced. It helps the user to suggest the items based on the user’s preferences. This system could help the students as Calculus is one of the tough subjects feared by most students. Credits given to the technology as many sources on the web can provide tutorials, working examples and solutions on the subjects. However, there are too many of them. Students had to make a few selections, which one can fulfil their needs of specific calculus topics. The personalized recommender system developed was a content-based filtering recommender system with its own scraping engine to collect the sources from the Internet which focuses on the basic Calculus topics. The system and engine were constructed by using Flask framework together with its relevant libraries. 

The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF

2021 ◽  
Vol 5 (5) ◽  
pp. 977-983
Author(s):  
Muhammad Johari ◽  
Arif Laksito
Keyword(s):  
Recommender System ◽  
Web Application ◽  
Information Filtering ◽  
Modern Society ◽  
The Internet ◽  
Hybrid Filtering ◽  
Hybrid Recommender System ◽  
Hybrid Recommender ◽  
Content Based Filtering ◽  
The Web

Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filtering to increase customers’ experience in social media and e-commerce. This research focuses on the combination of two methods in the recommender system, that is, demographic and content-based filtering, commonly it is called hybrid filtering. In this research, item products are collected using the data crawling method from the big three e-commerce in Indonesia (Shopee, Tokopedia, and Bukalapak). This experiment has been implemented in the web application using the Flask framework to generate products’ recommended items. This research employs the IMDb weight rating formula to get the best score lists and TF-IDF with Cosine similarity to create the similarity between products to produce related items.  

A cross-sectional survey among physicians on Internet use for epilepsy-related information (Preprint)

2019 ◽  
Author(s):  
Francesco Brigo ◽  
Simona Lattanzi ◽  
Giorgia Giussani ◽  
Laura Tassi ◽  
Nicola Pietrafusa ◽  
...  
Keyword(s):  
Internet Use ◽  
The Internet ◽  
Online Information ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Related Information ◽  
Internet Users ◽  
Therapeutic Decisions ◽  
The Individual ◽  
The Web

BACKGROUND The Internet has become one of the most important sources of health information, accessed daily by an ever-growing number of both patients and physicians, seeking medical advice and clinical guidance. A deeper insight into the current use of the Web as source of information on epilepsy would help in clarifying the individual attitude towards this medium by Internet users. OBJECTIVE We investigated views towards the Internet in a sample of Italian healthcare specialists involved in epilepsy field, to explore factors which explained the influence of information found on the internet. METHODS This study was a self-administered survey conducted in a group of members of the Italian Chapter of the International League Against Epilepsy (ILAE) in January 2018. RESULTS 184 questionnaires were analyzed. 97.8% of responders reported to seek online information on epilepsy. The Internet was most frequently searched to obtain new information (69.9%) or to confirm a diagnostic or therapeutic decision (37.3%). The influence of consulting the Internet on clinical practice was associated with registration to social network(s) (OR: 2.94; 95%CI: 1.28-6.76; p=0.011), higher frequency of Internet use (OR: 3.66; 95%CI: 1.56-9.21; p=0.006) and higher confidence in reliability of online information (OR: 2.61; 95%CI: 1.09-6.26; p=0.031). No association was found with age, sex, years in epilepsy practice or easiness to find online information. CONCLUSIONS Internet is frequently used among healthcare professionals involved in the epilepsy to obtain information about this disease. The attitude of being influenced by the Internet for diagnostic and/or therapeutic decisions in epilepsy is independent on age and years of experience in epilepsy, and probably reflects an individual approach towards the Web.

Digital India

2018 ◽  
pp. 170-184 ◽  
Author(s):  
Amit Kumar Sinha
Keyword(s):  
Mobile Devices ◽  
Rapid Growth ◽  
Low Cost ◽  
The Internet ◽  
Tier 2 ◽  
Internet Users ◽  
Tier 3 ◽  
Changing Demographics ◽  
Minimal Effort ◽  
The Web

E-commerce and internet businesses are driving the rapid growth of the domestic IT-ITeS industry, attracting unprecedented global interest and funding. Indian e-commerce and internet companies are growing rapidly with about 460 million internet users and a tele-density of around 85.2%. Increasing penetration of the internet, adoption of smartphones and minimal effort low-cost mobile devices, changing demographics, mobile-empowered youth, and the emergence of tier 2 and tier 3 cities as major shopping hubs have been driving the growth of the industry, with new retail forces shifting its dynamics. Furthermore, the continued growth of large pure-play organisations that are powerhouses has moved retailers' focus to the web channel. These companies are not only becoming gateways to product research, but have also introduced consumers to new ways of viewing the retail process.

Measuring Situational Anxiety Related to Information Retrieval on the Web Among English-Speaking Internet Users

2019 ◽  
Vol 31 (5) ◽  
pp. 480-491
Author(s):  
Carole Rodon ◽  
Anne Congard
Keyword(s):  
Information Retrieval ◽  
Complex Problem ◽  
The Internet ◽  
Internet Users ◽  
Sum Score ◽  
Affective Processes ◽  
Situational Anxiety ◽  
Internet Learning ◽  
English Speaking ◽  
The Web

Abstract Searching for information on the web is regarded as a complex problem-solving activity involving a range of cognitive and affective processes. Anxiety is a key affective factor. In this article, we describe the construction and initial validation stages of the Information Retrieval on the Web Anxiety Rate (IROWAR) scale. The final structure of this inventory was validated with a sample of 183 English-speaking Internet users. Reliability analyses indicated that the factors were internally consistent (Cronbach’s alpha: 0.92). When we checked divergent validity, we found negative correlations with both self-efficacy and positive attitude towards the Internet. There were no effects of either sex or age on the total IROWAR score, but the Internet search anxiety sum score decreased with the length of use. This scale will be useful in several domains, including research on the determinants of web anxiety, individuals’ experience of web anxiety and ways of supporting them and Internet learning.

scholarly journals Recommender System using Content Based Filtering for News Portal in Indonesia

2020 ◽  
Vol 8 (6) ◽  
pp. 173-178
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Recommender System ◽  
Information Overload ◽  
Cosine Similarity ◽  
News Article ◽  
The Internet ◽  
New Model ◽  
Digital Era ◽  
Content Based Filtering

Nowadays there is much news on the internet. It makes the reader become information overload. The reader does not know the most important news for them. The digital era, especially in Indonesia, generated data in Bahasa very fast that referred to as big data. Data mining by process big data can collect the data insight that the reader already read. This paper proposes a new model to proceed with Bahasa news and use the TF-IDF method to collect the feature of the article. Cosine similarity from the news article used to rank the new unknown articles to recommend articles based on their preference. we can filtering the stream of information and highlight the most likely article they will read but based on their preference that we already collect implicitly from the article that they read it, it’s a scroll depth of the article they read.Then we can serve the news more personalized from what they love to read.

scholarly journals A Genetic-Based Pairwise trip Planner Recommender System

2021 ◽  
Author(s):  
Nunung Nurul Qomariyah ◽  
Dimitar Kazakov
Keyword(s):  
Recommender System ◽  
Evaluation Study ◽  
Preference Elicitation ◽  
User Preference ◽  
Elicitation Method ◽  
Massive Growth ◽  
Internet Users ◽  
Pairwise Preference ◽  
Personalized Recommender System ◽  
Trip Planner

Abstract The massive growth of internet users nowadays can be a big opportunity for the businesses to promote their services. This opportunity is not only for e-commerce, but also for other e-services, such as e-tourism. In this paper, we propose an approach of personalized recommender system with pairwise preference elicitation for the e-tourism domain area. We used a combination of Genetic Agorithm with pairwise user preference elicitation approach. The advantages of pairwise preference elicitation method, as opposed to the pointwise method, have been shown in many studies, including to reduce incosistency and confusion of a rating number. We also performed a user evaluation study by inviting 24 participants to examine the proposed system and publish the POIs dataset which contains 201 attractions used in this study.

scholarly journals An Improved Recommender System Solution to Mitigate the Over-Specialization Problem Using Genetic Algorithms

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 242
Author(s):  
Oumaima Stitini ◽  
Soulaimane Kaloun ◽  
Omar Bencharef
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Recommender System ◽  
Fitness Functions ◽  
System Solution ◽  
Recommendation Algorithms ◽  
Alternative Approaches ◽  
Active Research ◽  
Content Based Filtering ◽  
Filtering Approach

Nowadays, recommendation systems offer a method of facilitating the user’s desire. It is useful for recommending items from a variety of areas such as in the e-commerce, medical, education, tourism, and industry domains. The e-commerce area represents the most active research we found, which assists users in locating the things they want. A recommender system can also provide users with helpful knowledge about things that could be of interest. Sometimes, the user gets bored with recommendations which are similar to their profiles, which leads to the over-specialization problem. Over-specialization is caused by limited content data, under which content-based recommendation algorithms suggest goods directly related to the customer profile rather than new things. In this study, we are particularly interested in recommending surprising, new, and unexpected items that may likely be enjoyed by users and will mitigate this limited content. In order to recommend novel and serendipitous items along with familiar items, we need to introduce additional hacks and note of randomness, which can be achieved using genetic algorithms that brings diversity to recommendations being made. This paper describes a Revolutionary Recommender System using a Genetic Algorithm called RRSGA which improves the fitness functions for recommending optimal results. The proposed approach employs a genetic algorithm to address the over-specialization issue of content-based filtering. The proposed method aims to incorporate genetic algorithms that bring variety to recommendations and efficiently adjust and suggest unpredictable and innovative things to the user. Experiments objectively demonstrate that our technology can recommend additional products that every consumer is likely to appreciate. The results of RRSGA have been compared against recommendation results from the content-based filtering approach. The results indicate the effectiveness of RRSGA and its capacity to make more accurate predictions than alternative approaches.

Providing Personalized Services to Users in a Recommender System

2015 ◽  
Vol 10 (2) ◽  
pp. 26-48 ◽  
Author(s):  
Olukunle Oduwobi ◽  
Bolanle Adefowoke Ojokoh
Keyword(s):  
Collaborative Filtering ◽  
Recommender System ◽  
Learning Ability ◽  
Learning Material ◽  
Electronic Library ◽  
Learning Materials ◽  
Personalized Services ◽  
E Learning ◽  
Personalized Recommender System ◽  
Content Based Filtering

Instructors recommend learning materials to a class of students not minding the learning ability and reading habit of each student. Learners are finding it problematic to make a decision about which available learning materials best meet their situation and will be beneficial to their course of study. In order to address this challenge, a new e-learning material recommender system that is able to recommend quality items to learners individually is required. The aim of this work is to develop a Personalized Recommender System that switches between Content-based and Collaborative filtering techniques, with an objective to design an algorithm to recommend electronic library materials, as well as personalize recommendations to both new and existing users. Experiments were conducted with evaluations showing that the recommender system was most effective when content-based filtering and collaborative filtering were used to recommend items for new users and existing users respectively, and still achieve personalization.

scholarly journals Spinning the Web of Hate Online: A Critical Review from the Malaysian Laws

2015 ◽  
Vol 11 (28) ◽  
pp. 183
Author(s):  
Dr. Syahirah Abdul Shukor ◽  
Associate Professor Dr. Nazura Abdul Manap
Keyword(s):  
Social Networking ◽  
Critical Review ◽  
The Internet ◽  
Internet Users ◽  
Sustainable Economy ◽  
The Future ◽  
The Law ◽  
Social Networking Website ◽  
The Web

<p>In a multi-cultural society, living in peace and tolerance are keys to development and sustainable economy. Undeniably, the efforts taken by all stakeholders are essential in materializing the future and dream of a peaceful country. Since its independence, Malaysia has been struggling to maintain the unity and integration of the three main ethnics, the Malays, the Chinese and the Indians. Matters pertaining to media especially publications of printed presses are strictly supervised by the Ministry of Home Affairs. However, with the inception of the Internet, regulating content of the Internet might be impossible for the law makers. This paper examines how the emergence of social networking website such as <em>Facebook, MySpace</em> and even <em>Tweeting</em> have been misused by irresponsible Internet users in Malaysia. Spinning the web of hate online is like spreading virus to the netizens and yet, its impact if it is not well tackled by members of society, it might spark serious problem to the unity and harmony of ethnics in Malaysia. Next, this paper examines how law responds to problems arose on the Internet. Finally, this paper suggests that supervision and monitoring content of the Internet which promote hate might be challenging but such problem need to be tackled by the authorities with extra vigilant and full coordination with all authorities.</p>

Internet Usage, Motives and Advertisements

2014 ◽  
Vol 5 (4) ◽  
pp. 37-49
Author(s):  
Manoocher Niknam ◽  
Kobra Najafi ◽  
Azamosadat Hoseini ◽  
Sima Amirpoor ◽  
Parisa Bahmandar ◽  
...  
Keyword(s):  
Online Advertising ◽  
Demographic Variables ◽  
Internet Usage ◽  
The Internet ◽  
Advertising Agencies ◽  
Significant Relation ◽  
Internet Users ◽  
Use Of Internet ◽  
To Receive ◽  
The Web

This study explains the internet usage among Iranian users. Therefore it has been tried to give basic answers to this question that: What is the Iranians main use for internet and not shopping online? Based on this, by thoroughly analyzing the literature of internet users and develop a comprehensive theoretical model, the use of internet was tested in the web domain. The results indicate that; there is a significant relation between the demographic variables (age, education) and the motivations for using the Internet, also results show that in Iran, men and women use the internet for more searching motivations, and one of the major reasons that Iranian users do not shop online is the mistrust to receive that product. This study was done on a descriptive–analytical basis and based on the achievements of this research, it was recommended to advertising agencies that by using the indicators identified how to make appropriate steps in order to provide online advertising.

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