My Career Story

2017 ◽  
Vol 26 (2) ◽  
pp. 308-321 ◽  
Author(s):  
Paul J. Hartung ◽  
Sara Santilli
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Future Research ◽  
Validity Study ◽  
Career Intervention ◽  
Self Reflection ◽  
Career Construction ◽  
Life Career ◽  
A Current ◽  
Life Design

My career story (MCS) comprises a self-guided autobiographical workbook designed to simulate career construction counseling. The MCS contains a series of questions from the Career Construction Interview to elicit a life-career story and reveal a life theme that are then related to a current career problem indicated by the workbook user. Reflecting on the answers to the questions aims to promote key life-design goals of adaptability, narratability, intentionality, and action. After describing its development and use, a case illustration and initial preliminary validity study of the MCS is presented. Latent semantic analysis, a method for determining meaning similarity of words and passages within bodies of text, indicated a mean agreement level of .81 between MCS life portraits constructed by participants ( N =10) and those constructed for the participants by experts in career construction counseling. The MCS shows some initial promise for self-guided career intervention to increase self-reflection and ability to tell and enact one’s career story. Future research is needed to support the validity of the MCS workbook.

Semantic Pattern Detection in Covid-19 using Contextual Clustering and Intelligent Topic Modeling

2022 ◽  
Vol 13 (2) ◽  
pp. 0-0
Keyword(s):  
Latent Semantic Analysis ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Pattern Detection ◽  
Future Research ◽  
Detection Approach ◽  
Semantic Spaces ◽  
And Control ◽  
The Impact

The Covid-19 pandemic is the deadliest outbreak in our living memory. So, it is need of hour, to prepare the world with strategies to prevent and control the impact of the epidemics. In this paper, a novel semantic pattern detection approach in the Covid-19 literature using contextual clustering and intelligent topic modeling is presented. For contextual clustering, three level weights at term level, document level, and corpus level are used with latent semantic analysis. For intelligent topic modeling, semantic collocations using pointwise mutual information(PMI) and log frequency biased mutual dependency(LBMD) are selected and latent dirichlet allocation is applied. Contextual clustering with latent semantic analysis presents semantic spaces with high correlation in terms at corpus level. Through intelligent topic modeling, topics are improved in the form of lower perplexity and highly coherent. This research helps in finding the knowledge gap in the area of Covid-19 research and offered direction for future research.

scholarly journals Semantic Pattern Detection in COVID-19 Using Contextual Clustering and Intelligent Topic Modeling

2022 ◽  
Vol 13 (2) ◽  
pp. 1-17
Author(s):  
Pooja Kherwa ◽  
Poonam Bansal
Keyword(s):  
Latent Semantic Analysis ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Pattern Detection ◽  
Future Research ◽  
Detection Approach ◽  
Semantic Spaces ◽  
And Control ◽  
The Impact

The Covid-19 pandemic is the deadliest outbreak in our living memory. So, it is need of hour, to prepare the world with strategies to prevent and control the impact of the epidemics. In this paper, a novel semantic pattern detection approach in the Covid-19 literature using contextual clustering and intelligent topic modeling is presented. For contextual clustering, three level weights at term level, document level, and corpus level are used with latent semantic analysis. For intelligent topic modeling, semantic collocations using pointwise mutual information(PMI) and log frequency biased mutual dependency(LBMD) are selected and latent dirichlet allocation is applied. Contextual clustering with latent semantic analysis presents semantic spaces with high correlation in terms at corpus level. Through intelligent topic modeling, topics are improved in the form of lower perplexity and highly coherent. This research helps in finding the knowledge gap in the area of Covid-19 research and offered direction for future research.

A Scoping Review of Life Design Intervention Research: Implications for Counselling and Psychotherapy Practice

2021 ◽  
Vol 55 (1) ◽  
pp. 138-157
Author(s):  
Bradley Lewis ◽  
José F. Domene
Keyword(s):  
Case Studies ◽  
Empirical Support ◽  
Social Constructionist ◽  
Career Counselling ◽  
Future Research ◽  
Career Adaptability ◽  
Balance Case ◽  
Career Construction ◽  
Life Design ◽  
Design Intervention

The recently developed paradigm in career counselling known as life design has caused a proliferation of new interventions. A scoping study was performed to provide an overview of empirical support for the effectiveness of these interventions. Twelve articles that evaluate the efficacy of eight interventions were found. Interventions included individual and group forms of the Career Construction Interview and My Career Story. Others were group-based life design interventions, the Career Construction Genogram, an online-based life design intervention, and a classroom intervention designed for elementary children. Career adaptability was the most commonly evaluated outcome and participants were most commonly from Italy, with no study using North American participants. Experimental or quasi-experimental research designs were most frequently used, while several articles reported on case studies. The authors recommend that future research balance case studies and experimental designs and that further research should validate findings with Canadian populations. This article notes the synergistic potential of engaging with social constructionist approaches in the broader field of counselling and psychotherapy for developing new interventions.

A review of career interventions from an educational perspective: Have investigations shed any light?

2000 ◽  
Vol 59 (4) ◽  
pp. 227-239 ◽  
Author(s):  
Lee-Ann Prideaux ◽  
Peter A. Creed ◽  
Juanita Muller ◽  
Wendy Patton
Keyword(s):  
Career Development ◽  
Intervention Studies ◽  
Future Research ◽  
Development Programs ◽  
Career Intervention ◽  
Career Interventions ◽  
International Trends ◽  
Specific Career ◽  
Education Interventions ◽  
Development Literature

Despite widespread acknowledgement of the importance of career development programs to assist students in their complex transition from school to work, very few specific career education interventions have been objectively evaluated. The aim of this paper is to highlight what the authors consider to be a conspicuous shortfall in the career development literature to date, that is, reports of methodologically sound career intervention studies carried out in actual high school settings. International trends in the world of work are briefly discussed in association with the repercussions these changes are producing for today's youth. The major portion of this article is devoted to a comprehensive review of career intervention studies with particular attention paid to the methodological and theoretical issues that resonate from this review process. Recommendations for future research are proposed.

The Conceptualization and Measurement of Job Crafting

2016 ◽  
Vol 60 (4) ◽  
pp. 173-186 ◽  
Author(s):  
Philipp Wolfgang Lichtenthaler ◽  
Andrea Fischbach
Keyword(s):  
Factor Structure ◽  
Work Engagement ◽  
Job Demands ◽  
Job Crafting ◽  
Future Research ◽  
Validity Study ◽  
German Version ◽  
Total N ◽  
Structure Reliability ◽  
German Speaking

Abstract. This research redefined the job demands–resources (JD-R) job crafting model ( Tims & Bakker, 2010 ) to resolve theoretical and empirical inconsistencies regarding the crafting of job demands and developed a German version of the Job Crafting Scale (JCS; Tims, Bakker, & Derks, 2012 ) in two separate studies (total N = 512). In Study 1 the German version of the JCS was developed and tested for its factor structure, reliability, and construct validity. Study 2 dealt with the validity of our redefined JD-R job crafting model. The results show that, like the original version, the German version comprises four job crafting types, and the German version of the JCS is a valid and reliable generic measure that can be used for future research with German-speaking samples. Evidence for the redefined JD-R job crafting model was based on findings relating job crafting to work engagement and emotional exhaustion.

Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words

2012 ◽  
Vol 132 (9) ◽  
pp. 1473-1480
Author(s):  
Masashi Kimura ◽  
Shinta Sawada ◽  
Yurie Iribe ◽  
Kouichi Katsurada ◽  
Tsuneo Nitta
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Spoken Words ◽  
Visual Scenes

Similarity Detection Using Latent Semantic Analysis Algorithm

2018 ◽  
Vol 6 (8) ◽  
pp. 102
Author(s):  
Priyanka R. Patil ◽  
Shital A. Patil
Keyword(s):  
Latent Semantic Analysis ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Mining Method ◽  
Research Papers ◽  
Information Measures ◽  
Automated Software ◽  
Day By Day ◽  
Ways Of Life ◽  
Dirichlet Allocation

Similarity View is an application for visually comparing and exploring multiple models of text and collection of document. Friendbook finds ways of life of clients from client driven sensor information, measures the closeness of ways of life amongst clients, and prescribes companions to clients if their ways of life have high likeness. Roused by demonstrate a clients day by day life as life records, from their ways of life are separated by utilizing the Latent Dirichlet Allocation Algorithm. Manual techniques can't be utilized for checking research papers, as the doled out commentator may have lacking learning in the exploration disciplines. For different subjective views, causing possible misinterpretations. An urgent need for an effective and feasible approach to check the submitted research papers with support of automated software. A method like text mining method come to solve the problem of automatically checking the research papers semantically. The proposed method to finding the proper similarity of text from the collection of documents by using Latent Dirichlet Allocation (LDA) algorithm and Latent Semantic Analysis (LSA) with synonym algorithm which is used to find synonyms of text index wise by using the English wordnet dictionary, another algorithm is LSA without synonym used to find the similarity of text based on index. LSA with synonym rate of accuracy is greater when the synonym are consider for matching.

Self-leadership Training Review

2019 ◽  
Author(s):  
Andrew Sidwell ◽  
Michael Perry
Keyword(s):  
Leadership Training ◽  
Future Research ◽  
Training Methods ◽  
Current State ◽  
A Current

The purpose of this article was to examine the current state of self-leadership training. The authors analyzed all published, publicly available studies (in English) pertaining to self-leadership training methods, offering a current state of self-leadership training, and implications for future research.

LATENT-SEMANTIC ANALYSIS, SOCIAL NETWORKS AND NON-STRUCTURED DATA: INTERACTION METHOD

2019 ◽  
Keyword(s):  
Social Networks ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Statistical Processing ◽  
Unstructured Data ◽  
Average Score ◽  
Text Type ◽  
Internet Users ◽  
The Matrix ◽  
Human Thinking

This article examines the method of latent-semantic analysis, its advantages, disadvantages, and the possibility of further transformation for use in arrays of unstructured data, which make up most of the information that Internet users deal with. To extract context-dependent word meanings through the statistical processing of large sets of textual data, an LSA method is used, based on operations with numeric matrices of the word-text type, the rows of which correspond to words, and the columns of text units to texts. The integration of words into themes and the representation of text units in the theme space is accomplished by applying one of the matrix expansions to the matrix data: singular decomposition or factorization of nonnegative matrices. The results of LSA studies have shown that the content of the similarity of words and text is obtained in such a way that the results obtained closely coincide with human thinking. Based on the methods described above, the author has developed and proposed a new way of finding semantic links between unstructured data, namely, information on social networks. The method is based on latent-semantic and frequency analyzes and involves processing the search result received, splitting each remaining text (post) into separate words, each of which takes the round in n words right and left, counting the number of occurrences of each term, working with a pre-created semantic resource (dictionary, ontology, RDF schema, ...). The developed method and algorithm have been tested on six well-known social networks, the interaction of which occurs through the ARI of the respective social networks. The average score for author's results exceeded that of their own social network search. The results obtained in the course of this dissertation can be used in the development of recommendation, search and other systems related to the search, rubrication and filtering of information.

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