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Journal articles on the topic 'Suggestion systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Buech, Veronika I. D., Alexandra Michel, and Karlheinz Sonntag. "Suggestion systems in organizations: what motivates employees to submit suggestions?" European Journal of Innovation Management 13, no. 4 (2010): 507–25. http://dx.doi.org/10.1108/14601061011086311.

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2

Frese, Michael, Eric Teng, and Cees J. D. Wijnen. "Helping to improve suggestion systems: predictors of making suggestions in companies." Journal of Organizational Behavior 20, no. 7 (1999): 1139–55. http://dx.doi.org/10.1002/(sici)1099-1379(199912)20:7<1139::aid-job946>3.0.co;2-i.

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3

Marx, Andrew E. "Management commitment for successful suggestion systems." Work Study 44, no. 3 (1995): 16–18. http://dx.doi.org/10.1108/00438029510085357.

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4

Schuring, Roel W., and Harald Luijten. "Reinventing suggestion systems for continuous improvement." International Journal of Technology Management 22, no. 4 (2001): 359. http://dx.doi.org/10.1504/ijtm.2001.002969.

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Gohary, Ali, Hamid Alizadeh, and Kambiz Heidarzadeh Hanzaee. "How co-creation uplift suggestion systems’ performance." Asia-Pacific Journal of Business Administration 8, no. 2 (2016): 197–222. http://dx.doi.org/10.1108/apjba-11-2015-0095.

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Purpose – Suggestion systems have always been used as the means of continuous development and co-creating values among the employees of organizations. On the other hand, the co-creation has been introduced as a solution to co-create values between companies and customers. Since a simultaneous study on setting up suggestion systems and co-creation among employees and customers have been ignored so far, the purpose of this paper, focussing on the combination of two strategies of suggestion systems (generally more effective among the employees of organizations) and co-creation (studied so far merely the scope of customers), is to evaluate variables leading to intention to use, improvement in understanding the concept of justice, and positive word-of-mouth. Design/methodology/approach – Two between-subjects experiments were carried out to explore the interactional role of co-creation, reward, and time in efficiency of suggestion systems. The first study which was carried out among customers analyzed the effect of setting up suggestion systems along with co-creation on the amount of their intention to use this system in the future and positive word-of-mouth. The second study discussed the effect of setting up suggestion systems along with co-creation on the level of understanding organizational justice and commitment. Findings – The results indicate that the effectiveness of co-creation and tangible factors, such as offered reward, on improving the evaluation of suggestion system. In the other word, when firm’s encourage customers to participate in value co-creation program in suggestion system, they perceive more justice and intend to participate more in such program in future. Originality/value – Most of the previous studies carried out on co-creation considered its effectiveness on occasions when a service failure occurs to consumers and the service provider urgently needs service recovery, but this paper aimed to provide a collaborative perspective toward co-creation through suggestion system that puts emphasis on service experience, innovation, and intention to future participation in such programs.

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Shapiro, James S. "A Consumerʼs Suggestion". Journal of Cataract & Refractive Surgery 14, № 2 (1988): 233. http://dx.doi.org/10.1016/s0886-3350(88)80105-6.

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Arif, Mohammed, Hani Aburas, Abdullah Al-Kuwaiti, and Dennis Kulonda. "Suggestion Systems: A Usability-Based Evaluation Methodology." Journal of King Abdulaziz University-Engineering Sciences 21, no. 2 (2010): 61–79. http://dx.doi.org/10.4197/eng.21-2.4.

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Kato, Makoto P., Tetsuya Sakai, and Katsumi Tanaka. "When do people use query suggestion? A query suggestion log analysis." Information Retrieval 16, no. 6 (2013): 725–46. http://dx.doi.org/10.1007/s10791-012-9216-x.

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Fröhlich, Julia Katharina. "Idea Selection in Suggestion Systems: A Thematic Perspective." Academy of Management Proceedings 2013, no. 1 (2013): 15644. http://dx.doi.org/10.5465/ambpp.2013.15644abstract.

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van Dijk, Christiaan, and Jan van den Ende. "Suggestion systems: transferring employee creativity into practicable ideas." R and D Management 32, no. 5 (2002): 387–95. http://dx.doi.org/10.1111/1467-9310.00270.

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Ferreira, Diogo, Mário Antunes, Diogo Gomes, and Rui L. Aguiar. "CLASSY: A Conversational Aware Suggestion System." Proceedings 31, no. 1 (2019): 40. http://dx.doi.org/10.3390/proceedings2019031040.

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Over the last few years, pervasive systems have seen some interesting development. Nevertheless, human–human interaction can also take advantage of those systems by using their ability to perceive the surrounding environment. In this work, we have developed a pervasive system – named CLASSY – that is aware of the conversational context and suggests documents potentially useful to the users based on an Information Retrieval system, and proposed a new scoring approach that uses semantics and distance based on proximity data in order to classify the relationship between tokens.

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Esch, Maria, Jinbo Chen, Stephan Weise, Keywan Hassani-Pak, Uwe Scholz, and Matthias Lange. "A Query Suggestion Workflow for Life Science IR-Systems." Journal of Integrative Bioinformatics 11, no. 2 (2014): 15–26. http://dx.doi.org/10.1515/jib-2014-237.

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Summary Information Retrieval (IR) plays a central role in the exploration and interpretation of integrated biological datasets that represent the heterogeneous ecosystem of life sciences. Here, keyword based query systems are popular user interfaces. In turn, to a large extend, the used query phrases determine the quality of the search result and the effort a scientist has to invest for query refinement. In this context, computer aided query expansion and suggestion is one of the most challenging tasks for life science information systems. Existing query front-ends support aspects like spelling correction, query refinement or query expansion. However, the majority of the front-ends only make limited use of enhanced IR algorithms to implement comprehensive and computer aided query refinement workflows. In this work, we present the design of a multi-stage query suggestion workflow and its implementation in the life science IR system LAILAPS. The presented workflow includes enhanced tokenisation, word breaking, spelling correction, query expansion and query suggestion ranking. A spelling correction benchmark with 5,401 queries and manually selected use cases for query expansion demonstrate the performance of the implemented workflow and its advantages compared with state-of-the-art systems.

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KAGAN, Robert, and Grzegorz KRZOS. "Economic Efficiency of Employee Suggestion Systems in Manufacturing Enterprises." Journal of Innovation and Business Best Practice 2021 (March 4, 2021): 1–14. http://dx.doi.org/10.5171/2021.936440.

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Full involvement of employees in improving enterprises and their processes is one of the flagship assumptions in modern management methods. A widely used solution supporting this approach is the employee suggestion systems (ESS), allowing the use of the intellectual potential and creativity of own staff.

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Froehlich, Julia K., Martin Hoegl, and Michael Gibbert. "Idea selection in suggestion systems: a thematic similarity perspective." R&D Management 46, no. 5 (2015): 887–99. http://dx.doi.org/10.1111/radm.12154.

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Zhou, Renjie, Samamon Khemmarat, Lixin Gao, et al. "Boosting video popularity through keyword suggestion and recommendation systems." Neurocomputing 205 (September 2016): 529–41. http://dx.doi.org/10.1016/j.neucom.2016.05.002.

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Martens, Willem H. J. "A Suggestion for Improvement of Current Psychiatric Diagnostic Systems." Psychopathology 34, no. 4 (2001): 217. http://dx.doi.org/10.1159/000049311.

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Rehman Khan, Haseeb Ur, Chen Kim Lim, Minhaz Farid Ahmed, Kian Lam Tan, and Mazlin Bin Mokhtar. "Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism." Sustainability 13, no. 15 (2021): 8141. http://dx.doi.org/10.3390/su13158141.

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Agenda 2030 of Sustainable Development Goals (SDGs) 9 and 11 recognizes tourism as one of the central industries to global development to tackle global challenges. With the transformation of information and communication technologies (ICT), e-tourism has evolved globally to establish commercial relationships using the Internet for offering tourism-related products, including giving personalised suggestions. The contextual suggestion has emerged as a modified recommendation system that is integrated with information-retrieval techniques within large databases to provide tourists with a list of suggestions based on contexts, such as location, time of day, or day of the week (weekdays or weekends). This study surveyed literature in the field of contextual suggestion and recommendation systems with a focus on e-tourism. The concerns linked with approaches used in contextual suggestion and recommendation systems are highlighted in this systematic review, while motivations, recommendations, and practical implications in e-tourism are also discussed in this paper. A query search using the keywords “contextual suggestion system”, “recommendation system”, and “tourism” identified 143 relevant articles published from 2012 to 2020. Four major repositories are considered for searching, namely, (i) Science Direct, (ii) Scopus, (iii) IEEE, and (iv) Web of Science. This review was carried out under the protocols of four phases, namely, (i) query searching in major article repositories, (ii) removal of duplicates, (iii) scan of title and abstract, and (iv) complete reading of articles. To identify the gaps in current research, a taxonomy analysis was exemplified into categories and subcategories. The main categories were highlighted as (i) review articles, (ii) model/framework, and (iii) applications. Critical analysis was carried out on the basis of the available literature on the limitations of approaches used in contextual suggestion and recommendation systems. In conclusion, the approaches used are mainly based on content-based filtering, collaborative filtering, preference-based product ranking, and language modelling. The evaluation measures for the contextual suggestion system include precision, normalized discounted cumulative, and mean reciprocal rank, while test collections comprise Internet resources. Given that the tourism industry contributed to the environmental and social-economic development, contextual suggestion and recommendation systems have presented themselves to be relevant in integrating and achieving SDG 9 and SDG 11 in many ways such as web-based e-services by the government sector and smart gadgets based on reliable and real-time data and information for city planners as well as law enforcement personnel in a sustainable city.

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Potocan, Vojko, Matjaz Mulej, and Stefan Kajzer. "Business cybernetics: a provocative suggestion." Kybernetes 34, no. 9/10 (2005): 1496–516. http://dx.doi.org/10.1108/03684920510614786.

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Steiger-Carçao, Adolfo, and L. M. Camarinha-Matos. "Concurrent Pascal as a robot level language – a suggestion." Robotica 4, no. 4 (1986): 269–72. http://dx.doi.org/10.1017/s0263574700009966.

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SUMMARYThis paper briefly describes actual robot level programming languages, focusing on their intrinsic limitations when compared with traditional concurrent programming languages or when used for robotic systems/flexible production workshops programming, and not only for an isolated manipulator control.To reduce such limitations, a suggestion is made to base the development of robotic programming systems on already existing concurrent languages (Concurrent Pascal, Modula-2), taking into account their built-in extension facilities for fastening the incorporation of (or easy interfacing with) existing packages or products already developed in robotics (robot models, CAD systems, vision systems, etc).Using such languages as a support base for a robotic station programming environment, with access to different components developed separately, will allow a better understanding of the inter-relations among components and their limitations when faced with an integration perspective.

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20

McDougal, Robert A., Isha Dalal, Thomas M. Morse, and Gordon M. Shepherd. "Automated Metadata Suggestion During Repository Submission." Neuroinformatics 17, no. 3 (2018): 361–71. http://dx.doi.org/10.1007/s12021-018-9403-z.

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21

Hägglund, Sture. "Introducing expert critiquing systems." Knowledge Engineering Review 8, no. 4 (1993): 281–84. http://dx.doi.org/10.1017/s0269888900000308.

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Expert critiquing systems present an interesting and important complement to conventional expert systems. The basic idea is to emphasize the support for the user's own decision making rather than to let the system independently suggest a solution to a given problem. Thus it is assumed that the user initially proposes a decision or course of action. The system then reviews this suggestion relative to known circumstance, tries to evaluate the proposed solution, provides suggestions for improvements, draws attention to possible risks, indicates alternatives, and evaluates their merits, etc. A critiquing system is characterized both by its approach to problem solving and by its style of interaction with the user, as will be detailed below.

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22

Taehyeon Doh. "Survey and Suggestion for Standardization of Online Catalog Retrieval Systems." Journal of Korean Library and Information Science Society 38, no. 4 (2007): 357–76. http://dx.doi.org/10.16981/kliss.38.4.200712.357.

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23

Recht, Ricardo, and Celeste Wilderom. "Kaizen and culture: on the transferability of Japanese suggestion systems." International Business Review 7, no. 1 (1998): 7–22. http://dx.doi.org/10.1016/s0969-5931(97)00048-6.

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24

Karthik, Valmeekam, Sarath Sreedharan, Sailik Sengupta, and Subbarao Kambhampati. "RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (2021): 16051–53. http://dx.doi.org/10.1609/aaai.v35i18.18009.

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Automated Planning techniques can be leveraged to build effective decision support systems that assist the human-in-the-loop. Such systems must provide intuitive explanations when the suggestions made by these systems seem inexplicable to the human. In this regard, we consider scenarios where the user questions the system's suggestion by providing alternatives (referred to as foils). In response, we empower existing decision support technologies to engage in an interactive explanatory dialogue with the user and provide contrastive explanations based on user-specified foils to reach a consensus on proposed decisions. To provide contrastive explanations, we adapt existing techniques in Explainable AI Planning (XAIP). Furthermore, we use this dialog to elicit the user's latent preferences and propose three modes of interaction that use these preferences to provide revised plan suggestions. Finally, we showcase a decision support system that provides all these capabilities.

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25

Takatsuka, T., S. Nishizaki, and Y. Yamamoto. "Necessity of extra repulsion in hypernuclear systems: Suggestion from neutron stars." European Physical Journal A 13, no. 1-2 (2002): 213–15. http://dx.doi.org/10.1140/epja1339-35.

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Marchal, C. "Number systems: A short history and a suggestion for future progress." Vistas in Astronomy 36 (January 1993): 191–202. http://dx.doi.org/10.1016/0083-6656(93)90121-y.

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Du Plessis, Andries J., Andrew Marx, and Gregory Wilson. "Generating Ideas and Managing Suggestion Systems in Organisations: Some Empirical Evidence." International Journal of Knowledge, Culture, and Change Management: Annual Review 8, no. 4 (2008): 133–40. http://dx.doi.org/10.18848/1447-9524/cgp/v08i04/50554.

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Sabari Mathavan, R. B., V. Rohitram, C. Ashhwath, and P. Sasikumar. "Drowsiness Detection and Rest Stop Suggestion." Journal of Physics: Conference Series 2115, no. 1 (2021): 012028. http://dx.doi.org/10.1088/1742-6596/2115/1/012028.

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Abstract In recent years, driving accidents have been increasing gradually, with most of them due to drowsiness. To tackle this problem, various methods and systems were developed to alert the driver behind the wheels, and to prevent accidents. A few approaches include heartbeat monitoring, pulse rate check, blink, and yawn detector. This paper discusses a driver mechanism, which is capable of detecting fatigue in real-time, using the Eye Aspect Ratio – EAR – parameter, and also provides a database with an interface for managers to track drivers. When the driver is tired, an email will also be sent to the manager. On the drivers’ side, there will be a buzzer noise to wake the driver up and nearby resting locations will be shown to the driver. Further, mapping to the nearby resting location of the driver’s choice is shown, if the driver feels too drowsy and feels the need for rest. It is essential to fabricate and construct this complete system via IoT and OpenCV methods to address this issue.

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Bozic, Bojan, Andre Rios, and Sarah Jane Delany. "Comparing tagging suggestion models on discrete corpora." International Journal of Web Information Systems 16, no. 2 (2020): 201–21. http://dx.doi.org/10.1108/ijwis-08-2019-0035.

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Purpose This paper aims to investigate the methods for the prediction of tags on a textual corpus that describes diverse data sets based on short messages; as an example, the authors demonstrate the usage of methods based on hotel staff inputs in a ticketing system as well as the publicly available StackOverflow corpus. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. Design/methodology/approach The paper consists of two parts: exploration of existing sample data, which includes statistical analysis and visualisation of the data to provide an overview, and evaluation of tag prediction approaches. The authors have included different approaches from different research fields to cover a broad spectrum of possible solutions. As a result, the authors have tested a machine learning model for multi-label classification (using gradient boosting), a statistical approach (using frequency heuristics) and three similarity-based classification approaches (nearest centroid, k-nearest neighbours (k-NN) and naive Bayes). The experiment that compares the approaches uses recall to measure the quality of results. Finally, the authors provide a recommendation of the modelling approach that produces the best accuracy in terms of tag prediction on the sample data. Findings The authors have calculated the performance of each method against the test data set by measuring recall. The authors show recall for each method with different features (except for frequency heuristics, which does not provide the option to add additional features) for the dmbook pro and StackOverflow data sets. k-NN clearly provides the best recall. As k-NN turned out to provide the best results, the authors have performed further experiments with values of k from 1–10. This helped us to observe the impact of the number of neighbours used on the performance and to identify the best value for k. Originality/value The value and originality of the paper are given by extensive experiments with several methods from different domains. The authors have used probabilistic methods, such as naive Bayes, statistical methods, such as frequency heuristics, and similarity approaches, such as k-NN. Furthermore, the authors have produced results on an industrial-scale data set that has been provided by a company and used directly in their project, as well as a community-based data set with a large amount of data and dimensionality. The study results can be used to select a model based on diverse corpora for a specific use case, taking into account advantages and disadvantages when applying the model to your data.

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Yoon, Ji Won, Keun Hae Park, and Minsun Kim. "A Suggestion of Sizing System for Industrial Full Body Harness." Research Institute of Human Ecology 27, no. 3 (2023): 185–97. http://dx.doi.org/10.36357/johe.2023.27.3.185.

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Background/Objectives: Industrial harness designs have traditionally prioritized safety and protection against physical impact while giving limited consideration to the wearer's body shape. To enhance the comfort of industrial harnesses, this study proposes domestic industrial harness sizing systems based on an analysis of Korean anthropometric measurements. Methods: Data from the 8th Size Korea anthropometric report(2020-2023) were utilized to propose sizing systems tailored to the Korean body type for industrial harness products. Dimensional analysis involved the direct measurement data of adult men and women aged 20 to 59. The sizing systems of commercially available industrial harnesses were also examined. The product from domestic brand with 3 sizes was selected as a representative design for further analysis. Results: Through an analysis of waist circumference frequency dis tribution, three sizes were determined: S (66- 161), M (81- 166), and L (96- 172). Conclusion/Implications: The industrial full body harness sizing system proposed in this study, based on Korean anthropometric measurements, is expected to enhance the fit of harnesses. Furthermore, this study is expected to offer essential data for establishing a rational sizing system from a producer's perspective. This research is significant as it represents the first effort to establish sizing systems for Koreans in full body harness design. Furthermore, it is anticipated that full body harness product designs using this system will not only improve user satisfaction with fit but also enhance ergonomic suitability.

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Et.al, Foo Yoke Ling. "Bus Ticketing System with Multiple Routes Suggestion." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 1816–24. http://dx.doi.org/10.17762/turcomat.v12i3.1010.

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An important part of the bus ticket booking system is the route. Online bus tickets are systems that integrate all the different bus organization routes. However, the existing online system only provides direct transportation to destinations. In many cases, customers will need to take some connecting buses before reaching their desired destination. Therefore, a multiple routes suggestion for bus ticketing system is introduced using an advance route generation algorithm. In addition to the basic features of the existing online system, the developed system offers recommended routes if the desired destination does not have a direct bus. The recommended route will be at several different bus operators and waiting time for the next route. The development of this system is expected to provide convenience for the customer to find multiple routes suggestion.

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Tahery, Saedeh, and Saeed Farzi. "Customized query auto-completion and suggestion — A review." Information Systems 87 (January 2020): 101415. http://dx.doi.org/10.1016/j.is.2019.101415.

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Sülün, Emre, Eray Tüzün, and Uğur Doğrusöz. "RSTrace+: Reviewer suggestion using software artifact traceability graphs." Information and Software Technology 130 (February 2021): 106455. http://dx.doi.org/10.1016/j.infsof.2020.106455.

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Guttiganur, Nagappa, Shivanand Aspalli, MuktaV Sanikop, Anupama Desai, Reetika Gaddale, and Archana Devanoorkar. "Classification systems for gingival recession and suggestion of a new classification system." Indian Journal of Dental Research 29, no. 2 (2018): 233. http://dx.doi.org/10.4103/ijdr.ijdr_207_17.

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Szabados, L. "Suggestion to Revise the Hipparcos-Parallax of Cepheids Belonging to Binary Systems." Highlights of Astronomy 11, no. 1 (1998): 580. http://dx.doi.org/10.1017/s1539299600022395.

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It has been suspected (Szabados 1997) that the apparent orbit of previously unresolved binaries involving a Cepheid component falsifies the Hipparcos-parallaxes deduced for these Cepheids. Since the incidence of binaries among Cepheids exceeds 50 per cent, this adverse effect on the parallax determination is a major error source.An obvious remedy is to repeat the determination of the five astrometric parameters for the Cepheids, members in binary systems, taking into accountthe orbital elements known from spectroscopic studies. This will result in more precise parallaxes and cosmic distance scale. Moreover, these Cepheidsare ideal targets for the future microarcsec astrometric missions.This study was partly supported by OTKA-grants T 014852 and T 022946.

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Yu, Clare C. "Why Study Noise Due to Two Level Systems: A Suggestion for Experimentalists." Journal of Low Temperature Physics 137, no. 3/4 (2004): 251–65. http://dx.doi.org/10.1023/b:jolt.0000049056.07100.85.

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Kim, Ji-Hoon, Sun-Young Cho, Sang-Yong Han, Sun-Dong Park, and Yun-Kyung Kim. "Suggestion about Modernized Classification of Herbal Medicinal Preparations in Dual Medical Systems." Journal of Korean Medicine 36, no. 1 (2015): 61–74. http://dx.doi.org/10.13048/jkm.15006.

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Fattahi, Rahmatollah, Mehri Parirokh, Mohammd Hosien Dayyani, Abdolrasoul Khosravi, and Mojgan Zareivenovel. "Effectiveness of Google keyword suggestion on users’ relevance judgment." Electronic Library 34, no. 2 (2016): 302–14. http://dx.doi.org/10.1108/el-03-2015-0035.

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Purpose – One of the most effective ways information retrieval (IR) systems including Web search engines can improve relevance performance is to provide their users with tools for facilitating query expansion. Search engines such as Google provide users with keyword suggest tools. This paper aims to investigate users’ criteria in relevance judgment regarding Google’s keywords suggest tool and to see how such keywords would lead to more relevant results from the viewpoint of users. Design/methodology/approach – Through a mixed method approach, quantitative and qualitative data were collected from 60 postgraduate students at Ferdowsi University of Mashhad, Iran, using four different instruments (questionnaire, thinking aloud technique, query logs and interviews). Findings – Among other criteria, the “relation between suggested keywords and the information need” (with the mean rate of 3.53 of four) was considered the most important by searchers in selecting suggested keywords for query expansion. Also, the “relation between suggested Keywords and the retrieved items” (with the mean rate of 3.62) was considered the second most important criterion in judging the relevance of the retrieved results. The participants agreed that the suggested keywords by Google improved the retrieval relevance. The content analysis of the participants’ aloud-thinking sessions and the interviews approved such findings. Originality/value – This research makes a contribution to the need of designers of IR systems regarding the use of add words for query expansion. It also helps librarians how to instruct searchers with expanding their queries to retrieve more relevant results. Another contribution of the study is the identification of a number of new relevance judgment criteria for Web-based environments.

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Salunke, Aniket, Ruchika Kukreja, Jayesh Kharche, and Amit Nerurkar. "Personalized Suggestion For Music Based On Collaborative Filtering." International Journal of Engineering and Computer Science 9, no. 05 (2020): 25047–51. http://dx.doi.org/10.18535/ijecs/v9i05.4487.

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With the advancement of technology there are millions of songs available on the internet and this creates problem for a person to choose from this vast pool of songs. So, there should be some middleman who must do this task on behalf of user and present most relevant songs that perfectly fits the user’s taste. This task is done by recommendation system. Music recommendation system predicts the user liking towards a particular song based on the listening history and profile. Most of the music recommendation system available today will give most recently played song or songs which have overall highest rating as suggestions to users but these suggestions are not personalized. The paper purposes how the recommendation systems can be used to give personalized suggestions to each and every user with the help of collaborative filtering which uses user similarity to give suggestions. The paper aims at implementing this idea and solving the cold start problem using content based filtering at the start.

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Jiang, Zijian, Ye Wang, Hao Zhong, and Na Meng. "Automatic method change suggestion to complement multi-entity edits." Journal of Systems and Software 159 (January 2020): 110441. http://dx.doi.org/10.1016/j.jss.2019.110441.

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Martinez Lerin, Pablo, Daisuke Yamamoto, and Naohisa Takahashi. "Mouse-Sensitive Following Path Suggestion for Drawing Travel Routes in Web Map Systems." Journal of Geographic Information System 04, no. 05 (2012): 393–402. http://dx.doi.org/10.4236/jgis.2012.45045.

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Vörös, Fanni, Zoltán Tompos, and Béla Kovács. "Examination of car navigation systems and UX designs – suggestion for a new interface." Proceedings of the ICA 2 (July 10, 2019): 1–7. http://dx.doi.org/10.5194/ica-proc-2-139-2019.

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<p><strong>Abstract.</strong> The need for car-related navigation and the appearance of the vehicles themselves are much the same age – of course. In the early days, paper maps and personal questioning were solved this problem. Nearly 100 years ago, the first built-in car GPS was released – and this is an innovation that is still an important part of car design. Planning the user interface is a very exciting issue, because only in a few seconds the display needs to provide the user with the right amount of information. In this research our goal was to assess Hungarians driving and built-in GPS using habits and based on this try to suggest the “perfect” interface. A questionnaire was made with 19 or 46 questions and more than 1000 respondents completed it. Because of the high number of questions only selected diagrams are represented. Some answers have also been subjected to different statistical tests.</p>

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Fishman, Lior, and David Simmons. "Intrinsic approximation for fractals defined by rational iterated function systems: Mahler's research suggestion." Proceedings of the London Mathematical Society 109, no. 1 (2014): 189–212. http://dx.doi.org/10.1112/plms/pdu002.

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Hull, F., K. Azumi, and R. Wharton. "Suggestion rates and sociotechnical systems in Japanese versus American factories: beyond quality circles." IEEE Transactions on Engineering Management 35, no. 1 (1988): 11–24. http://dx.doi.org/10.1109/17.6000.

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Hájek, P., B. Jakoubek, K. Kýhos, and T. Radil. "Increase in Cutaneous Temperature Induced by Hypnotic Suggestion of Pain." Perceptual and Motor Skills 74, no. 3 (1992): 737–38. http://dx.doi.org/10.2466/pms.1992.74.3.737.

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Eight patients with atopic eczema and six healthy subjects were given hypnotic suggestion to feel pain in the upper part of the back and in one case on the palm. An average local increase in skin temperature of 0.6° C (detected by thermovision) occurred under this condition. For some patients cutaneous pain threshold was increased before the experiment by means of repetitive hypnotic suggestion of analgesia. These subjects reported feeling no pain subjectively, but the local change in skin temperature was equal in both cases. The results suggest a central mechanism induced by measuring changes in pain threshold in the skin, which changes are independent of local changes in blood flow.

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Binsaleh, Muazzan, and Shahizan Hassan. "Systems Development Methodology for Mobile Commerce Applications." International Journal of Mobile Computing and Multimedia Communications 3, no. 4 (2011): 36–52. http://dx.doi.org/10.4018/jmcmc.2011100103.

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There are several methodologies, including traditional and agile methodologies, being utilized in current systems development. However, it could be argued that existing development methodologies may not be suitable for mobile commerce applications, as these applications are utilized in different contexts from fixed e-commerce applications. This study proposes a system development methodology for mobile commerce applications. In order to achieve this aim, four objectives are proposed: investigating existing systems development methodologies used to develop mobile commence applications, identifying strengths and weaknesses of existing development methodologies, construction of a suitable methodology for mobile commerce applications, and testing for its applicability and practicality. The research methodology used in the study is the design research, which includes the steps of awareness of problems, suggestion, development, evaluation and conclusion. However, this paper only focuses on the first two phases of the whole study, which are awareness of the problem and making suggestions, while the evaluation and conclusion will be conducted as future works.

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KOTEN, J. W., W. DEN OTTER;, and T. R. G. POOLE. "Suggestion for IL-2 treatment of conjunctival squamous carcinoma." British Journal of Ophthalmology 83, no. 8 (1999): 994b. http://dx.doi.org/10.1136/bjo.83.8.994b.

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Mustar, Agnès, Sylvain Lamprier, and Benjamin Piwowarski. "On the Study of Transformers for Query Suggestion." ACM Transactions on Information Systems 40, no. 1 (2022): 1–27. http://dx.doi.org/10.1145/3470562.

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When conducting a search task, users may find it difficult to articulate their need, even more so when the task is complex. To help them complete their search, search engine usually provide query suggestions. A good query suggestion system requires to model user behavior during the search session. In this article, we study multiple Transformer architectures applied to the query suggestion task and compare them with recurrent neural network (RNN)-based models. We experiment Transformer models with different tokenizers, with different Encoders (large pretrained models or fully trained ones), and with two kinds of architectures (flat or hierarchic). We study the performance and the behaviors of these various models, and observe that Transformer-based models outperform RNN-based ones. We show that while the hierarchical architectures exhibit very good performances for query suggestion, the flat models are more suitable for complex and long search tasks. Finally, we investigate the flat models behavior and demonstrate that they indeed learn to recover the hierarchy of a search session.

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Mozannar, Hussein, Gagan Bansal, Adam Fourney, and Eric Horvitz. "When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (2024): 10137–44. http://dx.doi.org/10.1609/aaai.v38i9.28878.

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AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (e.g., an IDE) with the aim of improving productivity. We pursue mechanisms for leveraging signals about programmers' acceptance and rejection of code suggestions to guide recommendations. We harness data drawn from interactions with GitHub Copilot, a system used by millions of programmers, to develop interventions that can save time for programmers. We introduce a utility-theoretic framework to drive decisions about suggestions to display versus withhold. The approach, conditional suggestion display from human feedback (CDHF), relies on a cascade of models that provide the likelihood that recommended code will be accepted. These likelihoods are used to selectively hide suggestions, reducing both latency and programmer verification time. Using data from 535 programmers, we perform a retrospective evaluation of CDHF and show that we can avoid displaying a significant fraction of suggestions that would have been rejected. We further demonstrate the importance of incorporating the programmer's latent unobserved state in decisions about when to display suggestions through an ablation study. Finally, we showcase how using suggestion acceptance as a reward signal for guiding the display of suggestions can lead to suggestions of reduced quality, indicating an unexpected pitfall.

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Choi, Yun-Hyuk, Hye-Yeon Choi, Chi-Seung Lee, Myung-Hyun Kim, and Jae-Myung Lee. "Suggestion of a design load equation for ice-ship impacts." International Journal of Naval Architecture and Ocean Engineering 4, no. 4 (2012): 386–402. http://dx.doi.org/10.3744/jnaoe.2012.4.4.386.

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