scholarly journals Application of Machine Learning in Google Services- A Case Study

2021 ◽  
pp. 24-37
Author(s):  
Siji Jose Pulluparambil ◽  
Subrahmanya Bhat
Keyword(s):  
Machine Learning ◽  
Search Engine ◽  
Case Study Research ◽  
Secondary Data ◽  
Important Variable ◽  
Machine Learning Algorithms ◽  
Survey Method ◽  
Future Outcomes ◽  
Google Search

Purpose: Google Search is currently the most preferred search engine worldwide, making it one of the websites with the highest traffic. It assists people in discovering the content they are searching for, from the large repository of the World Wide Web. Google has grown to be the best in the search engine market that it is the single most important variable to be considered when optimizing a website for search. There are many ranking algorithms used by Google to make the searching process more precise. Google has the vision “to provide access to the world's information in one click”. Machine learning is the most popular methodology applied in predicting future outcomes or organizing information to assist people in making required decisions.ML algorithms are trained over instances or examples through which they analyze the historical data available and learn from past experiences. By repeatedly training over the samples, the patterns in the data can be identified in order to make predictions about the future. Google, as an organization, can be a pioneer in ML, and as a technology product, can be a use case for machine learning. Here, a case analysis has been prepared on few applications of machine learning in the products and services of Google. Within this paper, we highlight their technological history, services with machine learning applications, financial plans, and challenges. The paper also tries to examine the various products of Google which apply ML, such as Google Maps, Gmail, Google Photos, Google Assistant, and review the algorithms used in each service. Approach: The detailed survey method on secondary data is used for analysing the data. Findings: Based on the developed case study, it is clearly evident that Google is using machine learning algorithms with few artificial intelligence features to enhance the quality of the services they provide. Originality: A new way of analysis was performed to identify the methods used in the organization’s services. Paper Type: Descriptive Case Study Research

scholarly journals Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study

10.2196/22637 ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. e22637
Author(s):  
Stephanie Aboueid ◽  
Samantha Meyer ◽  
James R Wallace ◽  
Shreya Mahajan ◽  
Ashok Chaurasia
Keyword(s):  
Young Adults ◽  
Search Engine ◽  
Case Study Research ◽  
Security And Privacy ◽  
Digital Platforms ◽  
Descriptive Case Study ◽  
Semistructured Interviews ◽  
Qualitative Descriptive ◽  
Google Search

Background Young adults often browse the internet for self-triage and diagnosis. More sophisticated digital platforms such as symptom checkers have recently become pervasive; however, little is known about their use. Objective The aim of this study was to understand young adults’ (18-34 years old) perspectives on the use of the Google search engine versus a symptom checker, as well as to identify the barriers and enablers for using a symptom checker for self-triage and self-diagnosis. Methods A qualitative descriptive case study research design was used. Semistructured interviews were conducted with 24 young adults enrolled in a university in Ontario, Canada. All participants were given a clinical vignette and were asked to use a symptom checker (WebMD Symptom Checker or Babylon Health) while thinking out loud, and were asked questions regarding their experience. Interviews were audio-recorded, transcribed, and imported into the NVivo software program. Inductive thematic analysis was conducted independently by two researchers. Results Using the Google search engine was perceived to be faster and more customizable (ie, ability to enter symptoms freely in the search engine) than a symptom checker; however, a symptom checker was perceived to be useful for a more personalized assessment. After having used a symptom checker, most of the participants believed that the platform needed improvement in the areas of accuracy, security and privacy, and medical jargon used. Given these limitations, most participants believed that symptom checkers could be more useful for self-triage than for self-diagnosis. Interestingly, more than half of the participants were not aware of symptom checkers prior to this study and most believed that this lack of awareness about the existence of symptom checkers hindered their use. Conclusions Awareness related to the existence of symptom checkers and their integration into the health care system are required to maximize benefits related to these platforms. Addressing the barriers identified in this study is likely to increase the acceptance and use of symptom checkers by young adults.

scholarly journals Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study (Preprint)

2020 ◽  
Author(s):  
Stephanie Aboueid ◽  
Samantha Meyer ◽  
James R Wallace ◽  
Shreya Mahajan ◽  
Ashok Chaurasia
Keyword(s):  
Young Adults ◽  
Search Engine ◽  
Case Study Research ◽  
Security And Privacy ◽  
Digital Platforms ◽  
Descriptive Case Study ◽  
Semistructured Interviews ◽  
Qualitative Descriptive ◽  
Google Search

BACKGROUND Young adults often browse the internet for self-triage and diagnosis. More sophisticated digital platforms such as symptom checkers have recently become pervasive; however, little is known about their use. OBJECTIVE The aim of this study was to understand young adults’ (18-34 years old) perspectives on the use of the Google search engine versus a symptom checker, as well as to identify the barriers and enablers for using a symptom checker for self-triage and self-diagnosis. METHODS A qualitative descriptive case study research design was used. Semistructured interviews were conducted with 24 young adults enrolled in a university in Ontario, Canada. All participants were given a clinical vignette and were asked to use a symptom checker (WebMD Symptom Checker or Babylon Health) while thinking out loud, and were asked questions regarding their experience. Interviews were audio-recorded, transcribed, and imported into the NVivo software program. Inductive thematic analysis was conducted independently by two researchers. RESULTS Using the Google search engine was perceived to be faster and more customizable (ie, ability to enter symptoms freely in the search engine) than a symptom checker; however, a symptom checker was perceived to be useful for a more personalized assessment. After having used a symptom checker, most of the participants believed that the platform needed improvement in the areas of accuracy, security and privacy, and medical jargon used. Given these limitations, most participants believed that symptom checkers could be more useful for self-triage than for self-diagnosis. Interestingly, more than half of the participants were not aware of symptom checkers prior to this study and most believed that this lack of awareness about the existence of symptom checkers hindered their use. CONCLUSIONS Awareness related to the existence of symptom checkers and their integration into the health care system are required to maximize benefits related to these platforms. Addressing the barriers identified in this study is likely to increase the acceptance and use of symptom checkers by young adults.

scholarly journals Conflict Between Hizb Ut-Tahrir And Islamic Civil Society In Indonesia:A Countermovement Approach

2020 ◽  
Vol 5 (2) ◽  
pp. 171-191
Author(s):  
Hasbi Aswar ◽  
Danial Bin Mohd. Yusof ◽  
Rohana Binti Abdul Hamid
Keyword(s):  
Social Movement ◽  
Case Study Research ◽  
Secondary Data ◽  
Political Mobilization ◽  
Status Quo ◽  
Political Narratives ◽  
The Status ◽  
Nahdlatul Ulama ◽  
Movement Study

In a social movement study, countermovement emerges when certain movement is considered to bring threat to the status quo or the current political and social condition. Social movement seeks for changing the existing situation while the countermovement pursues to keep it. As a result, the conflict between two becomes inevitable, where both will compete to win over the other. The existence of Hizb ut-Tahrir in Indonesia (HTI) for years is responded by some Islamic groups especially Nahdlatul Ulama (NU) and its allies, as threat to the Indonesian life due to the idea brought by HTI. It becomes the root of conflict between HTI and other Islamic groups in Indonesia. This article aims to explain the conflict between HTI and other Islamic groups by elaborating the effort of the Islamic groups to counter the HTI narratives and mobilization by using countermovement approach in social movement studies. This article is a case study research and using mainly secondary data to analyze the issue. This article found that Nahdlatul Ulama as the main countermovement played significant role to counter Hizb ut-Tahrir`s religious and political narratives as well as its political mobilization.

scholarly journals The Potential of Poverty in the City of Palangka Raya: Study SMIs Affected Pandemic Covid 19

2020 ◽  
Vol 3 (3) ◽  
pp. 1626-1634
Author(s):  
Pipit Anggriati Ningrum ◽  
Alexandra Hukom ◽  
Saputra Adiwijaya
Keyword(s):  
Qualitative Research ◽  
Case Study Research ◽  
Secondary Data ◽  
Study Research ◽  
Sales And Marketing ◽  
The Impact ◽  
The City ◽  
Depth Interviews ◽  
Detrimental Impact

This study aims to analyze the increasing potential for poverty in the city of Palangka Raya from the perspective of SMIs due to the impact of the 19th COVID pandemic. The data was obtained based on the results of in-depth interviews from February to April 2020 with 10 SMIs and supported from secondary data from the Central Statistics Agency. The data is processed based on qualitative research principles based on the type of case study research. In the results of this study it was found that the SMIs experienced a very detrimental impact in terms of sales and marketing of products so that employees who come to work are terminated indefinitely, in this connection it appears that there is potential increases in poverty that can occur in the future come.

scholarly journals Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety

2020 ◽  
Vol 27 (6) ◽  
pp. 929-933
Author(s):  
George Demiris ◽  
Kristin L Corey Magan ◽  
Debra Parker Oliver ◽  
Karla T Washington ◽  
Chad Chadwick ◽  
...  
Keyword(s):  
Machine Learning ◽  
Secondary Data ◽  
Health Indicators ◽  
Machine Learning Algorithms ◽  
Standardized Assessments ◽  
Learning Tools ◽  
Data Set ◽  
Problem Solving Therapy ◽  
Audio Communication ◽  
The Impact

Abstract Objective The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety. Materials and Methods We used a secondary data set generated by a clinical trial examining problem-solving therapy for hospice caregivers consisting of 140 transcripts of multiple, sequential conversations between an interviewer and a family caregiver along with standardized assessments of anxiety prior to each session; 98 of these transcripts (70%) served as the training set, holding the remaining 30% of the data for evaluation. Results A classifier for anxiety was developed relying on language-based features. An 86% precision, 78% recall, 81% accuracy, and 84% specificity were achieved with the use of the trained classifiers. High anxiety inflections were found among recently bereaved caregivers and were usually connected to issues related to transitioning out of the caregiving role. This analysis highlighted the impact of lowering anxiety by increasing reciprocity between interviewers and caregivers. Conclusion Verbal communication can provide a platform for machine learning tools to highlight and predict behavioral health indicators and trends.

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