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Journal articles on the topic 'Advice systems'

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Published: 10 December 2022

Last updated: 28 January 2023

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1

Mital, V. "Knowledge systems for financial advice." Knowledge Engineering Review 7, no. 3 (September 1992): 215–49. http://dx.doi.org/10.1017/s0269888900006354.

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AbstractThe financial domain has seen considerable knowledge Systems activity. Some of the efforts have resulted in deployable Systems, but many others have met with much less success. Commentators have attempted to discern broad, universal indicators which explain or predict success. More recently, however, it has become clearer that a principal cause of the difficultes encountered is the incongruence between the real world task and the System architecture employed by developers. Proceeding from the latter perspective, this paper concerns itself with knowledge Systems for the provision of investment related financial advice. The various tasks involved are differentiated and correlated to the System architectures employed by developers. It is seen that while simple rulebased Systems suffice for some tasks, others indicate the need for techniques such as Case-Based Design.

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2

van der Wees, J. G. L. "Juricas: Legal computer advice systems." Artificial Intelligence and Law 1, no. 4 (December 1992): 275–90. http://dx.doi.org/10.1007/bf00186724.

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3

Beyersdorff, Olaf, Johannes Köbler, and Sebastian Müller. "Proof systems that take advice." Information and Computation 209, no. 3 (March 2011): 320–32. http://dx.doi.org/10.1016/j.ic.2010.11.006.

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4

Kosheleva, Olga, and Vladik Kreinovich. "Advice to new instructors: systems approach." Mathematical Structures and Modeling, no. 3 (55) (December 4, 2020): 123–26. http://dx.doi.org/10.24147/2222-8772.2020.3.123-126.

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A recent paper provided useful system-based approach to new school teachers. In this paper, we somewhat modify this advice so that it can be applied to new instructors on all levels, including new instructors at the university level.

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5

Flynn, Allen J. "Theory of advice as an information object targeted at an unmade decision." Journal of Documentation 76, no. 1 (September 2, 2019): 212–30. http://dx.doi.org/10.1108/jd-05-2019-0099.

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Purpose The purpose of this paper is to advance an understanding of the concept of advice and its relationship to documents, information and knowledge. Design/methodology/approach A conceptual analysis of a sample of 48 relevant advice studies and two books, directly informed by documentation and information theories, was conducted to find out how researchers have approached advice conceptually since 1940. Further gains in understanding advice came from analyzing its relationship with environmental uncertainty. Findings Researchers have studied advice in the context of human-human, machine-machine and information and communication technology-intermediated interactions. Advice has been conceptualized and categorized in many different ways. Over time, conceptualizations of advice have broadened and become more general. In this light, it is theorized that advice is as an information object targeted at an unmade decision. This conceptualization of advice permits situated and momentary advice documents. A newly developed content-based framework of advice leads to an advice typology with four content-based categories of best possible advice: correct answers, probabilities, possibilities, and acknowledgments of the unknown. Research limitations/implications The refined advice theory, content-based advice framework and related typology of advice contributed here are small steps toward improved clarity about the nature of advice. These findings are limited in their focus to advice theory and advice categorization. Practical implications Scholars, practitioners and information system developers may reconsider advice theory and make use of the content-based framework and related advice typology in their work. These contributions will help advice-givers and the developers of advice-giving information systems and advice networks to provide better advice. Originality/value This paper fills a need for a clear and straightforward overall conceptualization of advice that accounts for advice documents and is informed by how advice has been previously conceptualized in multiple scientific fields.

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6

Gaston, Nicola. "Free up systems for funding and advice." Nature 508, no. 7494 (April 2014): 44. http://dx.doi.org/10.1038/508044b.

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7

Panou, Konstantinos, Panos Tzieropoulos, and Daniel Emery. "Railway driver advice systems: Evaluation of methods, tools and systems." Journal of Rail Transport Planning & Management 3, no. 4 (November 2013): 150–62. http://dx.doi.org/10.1016/j.jrtpm.2013.10.005.

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8

Maier, David, Rachel Pottinger, AnHai Doan, Eduard Dragut, Bill Howe, Joanne Lateulere, John Lateulere, et al. "Advice from SIGMOD/PODS 2020." ACM SIGMOD Record 49, no. 3 (December 17, 2020): 43–54. http://dx.doi.org/10.1145/3444831.3444841.

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9

Monereo, Carles. "Guidance systems, advice and counseling in school integration." Educar 8 (July 1, 1985): 71. http://dx.doi.org/10.5565/rev/educar.493.

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10

Traynor, Kate. "FDA seeks advice on track-and-trace systems." American Journal of Health-System Pharmacy 68, no. 7 (April 1, 2011): 552–54. http://dx.doi.org/10.2146/news110020.

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11

Will, Richard P., and Donald E. Hardaway. "Advice for Building Expert Systems: Precepts or Proverbs?" Interfaces 24, no. 6 (December 1994): 79–81. http://dx.doi.org/10.1287/inte.24.6.79.

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12

Carroll, John M., and Jean McKendree. "Interface design issues for advice-giving expert systems." Communications of the ACM 30, no. 1 (January 1987): 14–32. http://dx.doi.org/10.1145/7885.7886.

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13

Zabel, Diane. "Advice for Prospective Authors." Reference & User Services Quarterly 46, no. 2 (December 1, 2006): 4–5. http://dx.doi.org/10.5860/rusq.46n2.4.

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14

Abreu, José, Olga Ferrer-Roca, and Rodrigo Abreu. "Ophthalmological advice on the internet." Journal of Cataract & Refractive Surgery 25, no. 12 (December 1999): 1561–62. http://dx.doi.org/10.1016/s0886-3350(99)00317-x.

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15

Cesa-Bianchi, Nicolò, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, and Manfred K. Warmuth. "How to use expert advice." Journal of the ACM 44, no. 3 (May 1997): 427–85. http://dx.doi.org/10.1145/258128.258179.

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16

Bourne, J. R., H. H. Liu, C. D. Orogo, G. C. Collins, N. S. Uckun, and A. J. Brodersen. "Organizing and understanding beliefs in advice-giving diagnostic systems." IEEE Transactions on Knowledge and Data Engineering 3, no. 3 (1991): 269–80. http://dx.doi.org/10.1109/69.91058.

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17

Chik-Parnas, Lillian, Marius Dragomiroiu, and David Lorge Parnas. "A family of computer systems for delivering individualized advice." Knowledge-Based Systems 23, no. 7 (October 2010): 645–66. http://dx.doi.org/10.1016/j.knosys.2010.02.007.

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18

Chiffoleau, Yuna, and Jean-Marc Touzard. "Understanding local agri-food systems through advice network analysis." Agriculture and Human Values 31, no. 1 (May 16, 2013): 19–32. http://dx.doi.org/10.1007/s10460-013-9446-6.

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19

Fischer, Stanley. "Mundell-Fleming Lecture: Exchange Rate Systems, Surveillance, and Advice." IMF Staff Papers 55, no. 3 (July 2008): 367–83. http://dx.doi.org/10.1057/imfsp.2008.12.

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20

Fergenson, Laraine. "Advice to the Lovelorn." Critical Perspectives on Accounting 12, no. 6 (December 2001): 734. http://dx.doi.org/10.1006/cpac.2001.0514.

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21

Fraser, Donald C. "Advice for Reviewers." Journal of Guidance, Control, and Dynamics 9, no. 1 (January 1986): 1–3. http://dx.doi.org/10.2514/3.56401.

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22

Campbell, Merle, Mark Keil, and Maheshwar Boodraj. "The Impact of Behavioral Similarity on DSS Advice Acceptance." ACM SIGMIS Database: the DATABASE for Advances in Information Systems 53, no. 3 (July 25, 2022): 10–25. http://dx.doi.org/10.1145/3551783.3551786.

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Despite the many advantages that decision support systems (DSSs) provide to decision makers, acceptance of advice from these systems has remained relatively low. In this study, we leverage theoretical insights from the literature to build a DSS that is behaviorally similar to its user, with the aim of increasing acceptance of DSS advice. To test whether users would be more accepting of advice from a behaviorally-similar DSS, we conducted a field experiment in a complex semi-structured decision context. The results of our experiment provide empirical evidence that a behaviorally-similar DSS can increase acceptance of advice in semi-structured decision-making contexts.

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23

Lykouris, Thodoris, and Sergei Vassilvitskii. "Competitive Caching with Machine Learned Advice." Journal of the ACM 68, no. 4 (July 7, 2021): 1–25. http://dx.doi.org/10.1145/3447579.

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Traditional online algorithms encapsulate decision making under uncertainty, and give ways to hedge against all possible future events, while guaranteeing a nearly optimal solution, as compared to an offline optimum. On the other hand, machine learning algorithms are in the business of extrapolating patterns found in the data to predict the future, and usually come with strong guarantees on the expected generalization error. In this work, we develop a framework for augmenting online algorithms with a machine learned predictor to achieve competitive ratios that provably improve upon unconditional worst-case lower bounds when the predictor has low error. Our approach treats the predictor as a complete black box and is not dependent on its inner workings or the exact distribution of its errors. We apply this framework to the traditional caching problem—creating an eviction strategy for a cache of size k . We demonstrate that naively following the oracle’s recommendations may lead to very poor performance, even when the average error is quite low. Instead, we show how to modify the Marker algorithm to take into account the predictions and prove that this combined approach achieves a competitive ratio that both (i) decreases as the predictor’s error decreases and (ii) is always capped by O (log k ), which can be achieved without any assistance from the predictor. We complement our results with an empirical evaluation of our algorithm on real-world datasets and show that it performs well empirically even when using simple off-the-shelf predictions.

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24

Farias, Daniela Pucci De, and Nimrod Megiddo. "Combining expert advice in reactive environments." Journal of the ACM 53, no. 5 (September 2006): 762–99. http://dx.doi.org/10.1145/1183907.1183911.

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25

Azaria, Amos, Sarit Kraus Sarit Kraus, Claudia Goldman, and Omer Tsimhoni. "Advice Provision for Energy Saving in Automobile Climate Control Systems." Proceedings of the AAAI Conference on Artificial Intelligence 28, no. 2 (July 27, 2014): 2954–59. http://dx.doi.org/10.1609/aaai.v28i2.19021.

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Reducing energy consumption of climate control systems is important in order to reduce human environmental footprint. The need to save energy becomes even greater when considering an electric car, since heavy use of the climate control system may exhaust the battery. In this paper we consider a method for an automated agent to provide advice to drivers which will motivate them to reduce the energy consumption of their climate control unit. Our approach takes into account both the energy consumption of the climate control system and the expected comfort level of the driver. We therefore build two models, one for assessing the energy consumption of the climate control system as a function of the system’s settings, and the other, models human comfort level as a function of the climate control system’s settings. Using these models, the agent provides advice to the driver considering how to set the climate control system. The agent advises settings which try to preserve a high level of comfort while consuming as little energy as possible. We empirically show that drivers equipped with our agent which provides them with advice significantly save energy as compared to drivers not equipped with our agent.

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26

Ameri, Fatemeh, Kathleen Keeling, and Reza Salehnejad. "You Get What You Pay for on Health Care Question and Answer Platforms: Nonparticipant Observational Study." Journal of Medical Internet Research 22, no. 1 (January 15, 2020): e13534. http://dx.doi.org/10.2196/13534.

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Background Seeking health information on the internet is very popular despite the debatable ability of lay users to evaluate the quality of health information and uneven quality of information available on the Web. Consulting the internet for health information is pervasive, particularly when other sources are inaccessible because of time, distance, and money constraints or when sensitive or embarrassing questions are to be explored. Question and answer (Q&A) platforms are Web-based services that provide personalized health advice upon the information seekers’ request. However, it is not clear how the quality of health advices is ensured on these platforms. Objective The objective of this study was to identify how platform design impacts the quality of Web-based health advices and equal access to health information on the internet. Methods A total of 900 Q&As were collected from 9 Q&A platforms with different design features. Data on the design features for each platform were generated. Paid physicians evaluated the data to quantify the quality of health advices. Guided by the literature, the design features that affected information quality were identified and recorded for each Q&A platform. The least absolute shrinkage and selection operator and unbiased regression tree methods were used for the analysis. Results Q&A platform design and health advice quality were related. Expertise of information providers (beta=.48; P=.001), financial incentive (beta=.4; P=.001), external reputation (beta=.28; P=.002), and question quality (beta=.12; P=.001) best predicted health advice quality. Virtual incentive, Web 2.0 mechanisms, and reputation systems were not associated with health advice quality. Conclusions Access to high-quality health advices on the internet is unequal and skewed toward high-income and high-literacy groups. However, there are possibilities to generate high-quality health advices for free.

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27

De Brouwer, Philippe J. S. "Target-oriented investment advice." Journal of Asset Management 13, no. 2 (June 30, 2011): 102–14. http://dx.doi.org/10.1057/jam.2011.31.

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28

TOKAI, Akihiro. "PERSPECTIVE ON RISK ASSESSMENT AND MANAGEMENT AS ADVICE-GIVING SYSTEMS." ENVIRONMENTAL SYSTEMS RESEARCH 35 (2007): 279–85. http://dx.doi.org/10.2208/proer.35.279.

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29

Brown, Andrew D., and Hilary Roberts. "Implementing Information Systems: Some Practical Advice and a Richer Model." Creativity and Innovation Management 1, no. 3 (September 1992): 121–26. http://dx.doi.org/10.1111/j.1467-8691.1992.tb00039.x.

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30

Dawson, Patrick, Sarah Buckland, and Nigel Gilbert. "Expert Systems and the Public Provision of Welfare Benefit Advice." Policy & Politics 18, no. 1 (January 1, 1990): 43–54. http://dx.doi.org/10.1332/030557390782454602.

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31

Diamond, Patrick. "Polycentric governance and policy advice: lessons from Whitehall policy advisory systems." Policy & Politics 48, no. 4 (October 1, 2020): 563–81. http://dx.doi.org/10.1332/030557320x15870482509817.

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In countries worldwide, the provision of policy advice to central governments has been transformed by the deinstitutionalisation of policymaking, which has engaged a diverse range of actors in the policy process. Scholarship should therefore address the impact of deinstitutionalisation in terms of the scope and scale of policy advisory systems, as well as in terms of the influence of policy advisors. This article addresses this gap, presenting a programme of research on policy advice in Whitehall. Building on Craft and Halligan’s conceptualisation of a ‘policy advisory system’, it argues that in an era of polycentric governance, policy advice is shaped by ‘interlocking actors’ beyond government bureaucracy, and that the pluralisation of advisory bodies marginalises the civil service. The implications of such alterations are considered against the backdrop of governance changes, particularly the hybridisation of institutions, which has made policymaking processes complex, prone to unpredictability and at risk of policy blunders.

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32

Stockdale, Michael, and Rebecca Mitchell. "Legal advice privilege and artificial legal intelligence: Can robots give privileged legal advice?" International Journal of Evidence & Proof 23, no. 4 (July 16, 2019): 422–39. http://dx.doi.org/10.1177/1365712719862296.

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Legal professional privilege entitles parties to legal proceedings to object to disclosing communications. The form of legal professional privilege that is now commonly known as ‘legal advice privilege’ attaches to communications between a client and its lawyers in connection with the provision of legal advice. The provision of legal advice increasingly involves the use of technology across a wide spectrum of activities with varying degrees of human interaction or supervision. Use of technology ranges from a lawyer conducting a keyword search of a legal database to legal advice given online by fully automated systems. With technology becoming more integrated into legal practice, an important issue that has not been explored is whether legal advice privilege attaches to communications between client and legal services provider regardless of the degree of human involvement and even if the ‘lawyer’ might constitute a fully automated advice algorithm. In essence, our central research question is: If a robot gives legal advice, is that advice privileged? This article makes an original and distinctive contribution to discourse in this area through offering novel perspectives on and solutions to a question which has not previously been investigated by legal academics.

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33

Fraigniaud, Pierre, David Ilcinkas, and Andrzej Pelc. "Tree exploration with advice." Information and Computation 206, no. 11 (November 2008): 1276–87. http://dx.doi.org/10.1016/j.ic.2008.07.005.

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34

Fusco, Emanuele G., Andrzej Pelc, and Rossella Petreschi. "Topology recognition with advice." Information and Computation 247 (April 2016): 254–65. http://dx.doi.org/10.1016/j.ic.2016.01.005.

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35

Chen, Wan-Hui, and Paul P. Jovanis. "Driver En Route Guidance Compliance and Driver Learning with Advanced Traveler Information Systems: Analysis with Travel Simulation Experiment." Transportation Research Record: Journal of the Transportation Research Board 1843, no. 1 (January 2003): 81–88. http://dx.doi.org/10.3141/1843-10.

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If real-time driver en route guidance advice does not meet driver preferences (e.g., preference for taking the freeway) or the advice is not correct, drivers are very likely to ignore the information, and the guidance system becomes ineffective in their route choice no matter how advanced the system. There is a need to investigate the factors affecting driver compliance with en route guidance advice. A travel simulation experiment was used to investigate significant factors affecting driver route choice behavior. A linear mixed model was developed for describing the factors affecting driver compliance with guidance advice using the compliance rate over several simulated trips as a dependent variable. The issue of repeated observations is addressed. The system accuracy and subjects’ learning experience in their spatial experience at the same intersection and temporal experience in the same day are also taken into account. The model results show that significant factors are involved: freeway advice, turning advice, congestion occurrence, incident occurrence, subjects’ spatial experience, subjects’ temporal experience, and subjects’ education level; there are several important interactions as well.

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36

Klein, Gary, and James J. Jiang. "User perception of expert system advice." Journal of Systems and Software 48, no. 2 (October 1999): 155–61. http://dx.doi.org/10.1016/s0164-1212(99)00053-9.

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37

Yang, Ji Yeon, and Soo Young Rieh. "Dual roles in information mediation at work: Analysis of advice-receiving and advice-providing diary surveys." Proceedings of the American Society for Information Science and Technology 49, no. 1 (2012): 1–4. http://dx.doi.org/10.1002/meet.14504901263.

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38

Fang, Hang, Min Zhang, Chongshun Zhao, Xia Yao, Haizhen Wang, Hailing Xia, and Min Yu. "Characteristics of length of stay and cardiovascular pharmacotherapy advice among chronic obstructive pulmonary disease patients." Science Progress 104, no. 4 (October 2021): 003685042110660. http://dx.doi.org/10.1177/00368504211066003.

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Chronic obstructive pulmonary disease (COPD) increases the global disease burden due to its diverse adverse health effects on the respiratory and cardiovascular systems. This study aimed to elucidate the potential indicators of length of stay (LOS) and pharmacotherapy advice among COPD patients. Thereafter, hospitalized COPD patients with clinical records and respiratory and cardiovascular pharmacotherapy advice were retrospectively collected from a tertiary hospital between April 2017 and September 2020, and the determinants of LOS and cardiovascular pharmacotherapy advice were explored using regression analyses. Overall, 475 patients with COPD were recruited and stratified according to exacerbation and presence of Cor pulmonale (CP). The extended LOS, increased B-type natriuretic peptides (BNP), and a higher percentage of cardiovascular pharmacotherapy advice were observed in COPD with CP regardless of exacerbation, although the percentage of respiratory prescriptions was comparable. The presence of CP indicated a longer LOS ( B = 1.850, p < 0.001) for COPD regardless of exacerbation. Meanwhile, elevated BNP levels indicated cardiovascular pharmacotherapy advise for both COPD in exacerbation (OR = 1.003, p = 0.012) and absence of exacerbation (OR = 1.006, p = 0.015). Moreover, advice for trimetazidine use for COPD in exacerbation (OR = 1.005, p = 0.002) has been suggested. Therefore, CP appears to be an important comorbidity resulting in extended LOS for COPD, which is likely to be advised with cardiovascular pharmacotherapy, which might be guided through BNP monitoring.

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39

Santoro, Cerice. "Advice for a Communicative Learning Environment." Westcliff International Journal of Applied Research 1, no. 1 (April 1, 2017): 37–45. http://dx.doi.org/10.47670/wuwijar201711cs.

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Currently the Philippines is the last country in Asia implementing a ten year education plan providing education until tenth grade before students reach university level. The education change will aid future Filipino professionals to compete globally since it is the recognized standard throughout the world. However, with expanding pressure for EFL teachers to implement new programs and systems it has left a gap between students being proficient academically and communicatively at the same time. The issue continues to increase since inappropriate implementation of activities leave students perceiving the communicative approach as frivolous and unproductive. As a result students do not appreciate an active learning environment in the classroom.

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40

Sparrow, LA. "A review of fertiliser advice in Australia." Australian Journal of Experimental Agriculture 33, no. 8 (1993): 1067. http://dx.doi.org/10.1071/ea9931067.

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Fertiliser advice is provided in many ways in Australia today. There has been a move away from blanket recommendations to recommendations for particular paddock-crop-farmer combinations. Emphasis has been on phosphorus for pastures and on nitrogen and phosphorus for cereals because of the importance of these elements and production systems in Australian agriculture. Soil tests are a major tool used in formulating recommendations, but plant tissue testing and nutrient budgets are playing increasing roles both in addition, and as alternatives, to soil tests. Variability within our agricultural systems places limits on the capacity of any or all of these techniques to predict precise fertiliser needs. We know very little about farmer attitudes to fertiliser advice, both for the minority of farmers who use advisory services and, more so, for the majority who do not. Farmers have not been questioned enough about why they have, or have not, adopted available technology. If better fertiliser management is to be more widely practised, the needs of our clients must direct future research and extension in soil fertility more than they have in the past. Resources for research will be increasingly difficult to justify unless serious consideration is given to the application of that research in agriculture and its adoption by farmers.

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41

Neve, J. J., W. E. M. Korten, F. F. Jorritsma, G. F. Kinds, and Ch P. Legein. "The Visual Advice Centre, Eindhoven, The Netherlands." Documenta Ophthalmologica 82, no. 1-2 (1992): 15–23. http://dx.doi.org/10.1007/bf00156988.

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42

Maggs, Peter B. "Free Legal Advice on the Internet." International Journal of Legal Information 34, no. 3 (2006): 483–512. http://dx.doi.org/10.1017/s0731126500001712.

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On numerous online discussion forums in various countries, ordinary people pose specific legal questions and both ordinary people and lawyers answer them. This article considers this new and rapidly growing method of providing legal advice. It emphasizes qualitative over quantitative issues. It seeks to answer questions such as “What kind of questions are being asked?”; “What sort of people are giving legal advice?”, “What sort of people are getting legal advice?”. For those few legal systems that I know something about, I also have considered the question, “How good is the advice?” This is a comparative study, involving discussion forums for Armenian, Australian, Austrian, Brazilian, Canadian, Croatian, English, French, German, Italian, Moldovan, Portuguese, Russian, Scots, Spanish, Swiss, Ukrainian, United Kingdom, and United States law.

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43

Olstam, Johan, Viktor Bernhardsson, Charisma Choudhury, Gerdien Klunder, Isabel Wilmink, and Martijn van Noort. "Modelling Eco-Driving Support System for Microscopic Traffic Simulation." Journal of Advanced Transportation 2019 (December 25, 2019): 1–16. http://dx.doi.org/10.1155/2019/2162568.

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Microscopic traffic simulation is an ideal tool for investigating the network level impacts of eco-driving in different networks and traffic conditions, under varying penetration rates and driver compliance rates. The reliability of the traffic simulation results however rely on the accurate representation of the simulation of the driver support system and the response of the driver to the eco-driving advice, as well as on a realistic modelling and calibration of the driver’s behaviour. The state-of-the-art microscopic traffic simulation models however exclude detailed modelling of the driver response to eco-driver support systems. This paper fills in this research gap by presenting a framework for extending state-of-the-art traffic simulation models with sub models for drivers’ compliance to advice from an advisory eco-driving support systems. The developed simulation framework includes among others a model of driver’s compliance with the advice given by the system, a gear shifting model and a simplified model for estimating vehicles maximum possible acceleration. Data from field operational tests with a full advisory eco-driving system developed within the ecoDriver project was used to calibrate the developed compliance models. A set of verification simulations used to illustrate the effect of the combination of the ecoDriver system and drivers’ compliance to the advices are also presented.

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44

Droste-Franke, Bert. "Challenges and potential improvements of systems analyses for sector coupling." TATuP - Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 29, no. 2 (July 17, 2020): 45–51. http://dx.doi.org/10.14512/tatup.29.2.45.

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This paper discusses the challenges of systems analysis for policy advice in the context of sector coupling along the three dimensions of socio-technical problems: control, change, and action. Research shows that the challenges of systems analyses increase significantly when considering sector coupling, both with respect to the choice of areas of investigation and with respect to the basic methods and practices of systems analysis for policy advice. In particular, social aspects and practical expertise need to be considered, results of different studies should ideally be combinable for reflexive meta-analyses, and analyses should focus on key messages.

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45

Jain, Seema, Scott D. Rothenberger, Wendy L. Bennett, Jeanne M. Clark, Molly B. Conroy, Sharon J. Herring, Jennifer L. Kraschnewski, et al. "Provider Advice and Patient Perceptions on Weight Across Five Health Systems." American Journal of Preventive Medicine 59, no. 3 (September 2020): e105-e114. http://dx.doi.org/10.1016/j.amepre.2020.03.013.

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46

Jones, J., and M. Virvou. "User modelling and advice giving in intelligent help systems for Unix." Information and Software Technology 33, no. 2 (March 1991): 121–33. http://dx.doi.org/10.1016/0950-5849(91)90057-i.

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47

Craft, Jonathan, and Michael Howlett. "Policy formulation, governance shifts and policy influence: location and content in policy advisory systems." Journal of Public Policy 32, no. 2 (June 15, 2012): 79–98. http://dx.doi.org/10.1017/s0143814x12000049.

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AbstractMost studies of policy formulation focus on the nature and kind of advice provided to decision-makers and think of this as originating from a system of interacting elements: a “policy advisory system”. Policy influence in such models has historically been viewed as based on considerations of the proximate location of policy advisors vis à vis the government, linked to related factors such as the extent to which governments are able to control sources of advice. While not explicitly stated, this approach typically presents the content of policy advice as either partisan “political” or administratively “technical” in nature. This article assesses the merits of these locational models against evidence of shifts in governance arrangements that have blurred both the inside vs outside and technical vs political dimensions of policy formulation environments. It argues that the growing plurality of advisory sources and the polycentrism associated with these governance shifts challenge the utility of both the implied content and locational dimensions of traditional models of policy advice systems. A revised approach is advanced that sees influence more as a product of content than location. The article concludes by raising several hypotheses for future research linking advisory system behaviour to governance arrangements.

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Bouraga, Sarah, Ivan Jureta, Stéphane Faulkner, and Caroline Herssens. "Knowledge-Based Recommendation Systems." International Journal of Intelligent Information Technologies 10, no. 2 (April 2014): 1–19. http://dx.doi.org/10.4018/ijiit.2014040101.

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Knowledge-Base Recommendation (or Recommender) Systems (KBRS) provide the user with advice about a decision to make or an action to take. KBRS rely on knowledge provided by human experts, encoded in the system and applied to input data, in order to generate recommendations. This survey overviews the main ideas characterizing a KBRS. Using a classification framework, the survey overviews KBRS components, user problems for which recommendations are given, knowledge content of the system, and the degree of automation in producing recommendations.

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Glasser, Sarah. "Judging Big Deals: Challenges, Outcomes, and Advice." Journal of Electronic Resources Librarianship 25, no. 4 (October 2013): 263–76. http://dx.doi.org/10.1080/1941126x.2013.847672.

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Kierulff, Herbert, and Henry L. Petersen. "Finance is everything: advice from turnaround managers." Journal of Business Strategy 30, no. 6 (October 30, 2009): 44–51. http://dx.doi.org/10.1108/02756660911003112.

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