Modeling of Decision Trees Through P systems

[EN] In this paper, we propose a decision-tree modeling in the framework of membrane computing. We propose an algorithm to obtain a P system that is equivalent to any decision tree taken as input. In our case, and unlike previous proposals, we formulate the concepts of decision trees endogenously, since there is no external agent involved in the modeling. The tree structure can be defined naturally by the topology of the regions in the P system and the decision rules are defined by communication rules of the P system.Sempere Luna, JM. (2019). Modeling of Decision Trees Through P systems. New Generation Computing. 37(3):325-337. https://doi.org/10.1007/s00354-019-00052-4325337373Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman & Hall, Boca Raton (1984)Cardona, M., Colomer, M.A., Margalida, A., Palau, A., Pérez-Hurtado, I., Pérez-Jiménez, M.J., Sanuy, D.: A computational modeling for real ecosystems based on P systems. Nat. Comput. 10(1), 39–53 (2011)Cecilia, J.M., García, J.M., Guerrero, G.D., Martínez-del-Amor, M.A., Pérez-Hurtado, I., Pérez-Jiménez, M.J.: Simulation of P systems with active membranes on CUDA. Brief. Bioinform. 11(3), 313–322 (2010)Díaz-Pernil, D., Peña-Cantillana, F., Gutiérrez-Naranjo, M.A.: Self-constructing Recognizer P Systems. In: Proceedings of the Thirteenth Brainstorming Week on Membrane Computing. Fénix Editora, pp. 137–154 (2014)Fayyad, U.M., Irani, K.B.: On the handling of continuous-valued attributes in decision tree generation. Mach. Learn. 8, 87–102 (1992)Kingsford, C., Salzberg, S.L.: What are decision trees ? Nat. Biotechnol. 26(9), 1011–1013 (2008)Martín-Vide, C., Păun, Gh, Pazos, J., Rodríguez-Patón, A.: Tissue P systems. Theor. Comput. Sci. 296, 295–326 (2003)Martínez-del-Amor, M.A., García-Quismondo, M., Macías-Ramos, L.F., Valencia-Cabrera, L., Riscos-Núñez, A., Pérez-Jiménez, M.J.: Simulating P systems on GPU devices: a survey. Fund. Inf. 136(3), 269–284 (2015)Mitchell, T.: Machine Learning. McGraw-Hill, New York City (1997)Păun, Gh: Membrane Computing, An Introduction. Springer, Berlin (2002)Păun, Gh, Rozenberg, G., Salomaa, A. (eds.): The Oxford Handbook of Membrane Computing. Oxford University Press, Oxford (2010)Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, Burlington (1993)Sempere, J.M.: A View of P systems from information theory. In: Proceedings of the 17th international conference on membrane computing (CMC 2016) LNCS vol. 10105. Springer, pp. 352–362 (2017)Sammut, C., Webb, G.I. (eds.): Encyclopedia of Machine Learning. Springer, Berlin (2011)Wang, J., Hu, J., Peng, H., Pérez-Jiménez, M.J., Riscos-Núñez, A.: Decision tree models induced by membrane systems. Rom. J. Inf. Sci. Technol. 18(3), 228–239 (2015)Zhang, C., Ma, Y. (eds.): Ensemble Machine Learning, Methods and Applications. Springer, Berlin (2012)Zhang, X., Wang, B., Ding, Z., Tang, J., He, J.: Implementation of membrane algorithms on GPU. J. Appl. Math. 2014, 7 (2014

Wikipedia vandalism detection: combining natural language, metadata, and reputation features

Wikipedia is an online encyclopedia which anyone can edit. While most edits are constructive, about 7% are acts of vandalism. Such behavior is characterized by modifications made in bad faith; introducing spam and other inappropriate content. In this work, we present the results of an effort to integrate three of the leading approaches to Wikipedia vandalism detection: a spatio-temporal analysis of metadata (STiki), a reputation-based system (WikiTrust), and natural language processing features. The performance of the resulting joint system improves the state-of-the-art from all previous methods and establishes a new baseline for Wikipedia vandalism detection. We examine in detail the contribution of the three approaches, both for the task of discovering fresh vandalism, and for the task of locating vandalism in the complete set of Wikipedia revisions.The authors from Universitat Politècnica de València thank also the MICINN research project TEXT-ENTERPRISE 2.0 TIN2009-13391-C04-03 (Plan I+D+i). UPenn contributions were supported in part by ONR MURI N00014-07-1-0907. This research was partially supported by award 1R01GM089820-01A1 from the National Institute Of General Medical Sciences, and by ISSDM, a UCSC-LANL educational collaboration.Adler, BT.; Alfaro, LD.; Mola Velasco, SM.; Rosso, P.; West, AG. (2011). Wikipedia vandalism detection: combining natural language, metadata, and reputation features. En Computational Linguistics and Intelligent Text Processing. 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Notebook Papers of CLEF 2010 LABs and Workshops, Padua, Italy, September 22-23 (2010)Adler, B., de Alfaro, L., Pye, I.: Detecting Wikipedia Vandalism using WikiTrust. In: Braschler, M., Harman, D. (eds.) Notebook Papers of CLEF 2010 LABs and Workshops, Padua, Italy, September 22-23 (2010)West, A.G., Kannan, S., Lee, I.: Detecting Wikipedia Vandalism via Spatio-Temporal Analysis of Revision Metadata. 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ECIR 2008. LNCS, vol. 4956, pp. 663–668. Springer, Heidelberg (2008)Smets, K., Goethals, B., Verdonk, B.: Automatic Vandalism Detection in Wikipedia: Towards a Machine Learning Approach. In: WikiAI 2008: Proceedings of the Workshop on Wikipedia and Artificial Intelligence: An Evolving Synergy, pp. 43–48. AAAI Press, Menlo Park (2008)Druck, G., Miklau, G., McCallum, A.: Learning to Predict the Quality of Contributions to Wikipedia. In: WikiAI 2008: Proceedings of the Workshop on Wikipedia and Artificial Intelligence: An Evolving Synergy, pp. 7–12. AAAI Press, Menlo Park (2008)Itakura, K.Y., Clarke, C.L.: Using Dynamic Markov Compression to Detect Vandalism in the Wikipedia. In: SIGIR 2009: Proc. of the 32nd Intl. ACM Conference on Research and Development in Information Retrieval, pp. 822–823 (2009)Chin, S.C., Street, W.N., Srinivasan, P., Eichmann, D.: Detecting Wikipedia Vandalism with Active Learning and Statistical Language Models. In: WICOW 2010: Proc. of the 4th Workshop on Information Credibility on the Web (April 2010)Zeng, H., Alhoussaini, M., Ding, L., Fikes, R., McGuinness, D.: Computing Trust from Revision History. In: Intl. Conf. on Privacy, Security and Trust (2006)McGuinness, D., Zeng, H., da Silva, P., Ding, L., Narayanan, D., Bhaowal, M.: Investigation into Trust for Collaborative Information Repositories: A Wikipedia Case Study. In: Proc. of the Workshop on Models of Trust for the Web (2006)Adler, B., de Alfaro, L.: A Content-Driven Reputation System for the Wikipedia. In: WWW 2007: Proceedings of the 16th International World Wide Web Conference. ACM Press, New York (2007)Belani, A.: Vandalism Detection in Wikipedia: a Bag-of-Words Classifier Approach. Computing Research Repository (CoRR) abs/1001.0700 (2010)Potthast, M., Stein, B., Holfeld, T.: Overview of the 1st International Competition on Wikipedia Vandalism Detection. In: Braschler, M., Harman, D. (eds.) 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Computational Strategies for Scalable Genomics Analysis.

The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data technologies have been explored to scale up/out current bioinformatics solutions to mine the big genomics data. In this review, we survey some of these exciting developments in the applications of parallel distributed computing and special hardware to genomics. We comment on the pros and cons of each strategy in the context of ease of development, robustness, scalability, and efficiency. Although this review is written for an audience from the genomics and bioinformatics fields, it may also be informative for the audience of computer science with interests in genomics applications

Beyond opening up the black box: Investigating the role of algorithmic systems in Wikipedian organizational culture

Scholars and practitioners across domains are increasingly concerned with algorithmic transparency and opacity, interrogating the values and assumptions embedded in automated, black-boxed systems, particularly in user-generated content platforms. I report from an ethnography of infrastructure in Wikipedia to discuss an often understudied aspect of this topic: the local, contextual, learned expertise involved in participating in a highly automated social-technical environment. Today, the organizational culture of Wikipedia is deeply intertwined with various data-driven algorithmic systems, which Wikipedians rely on to help manage and govern the "anyone can edit" encyclopedia at a massive scale. These bots, scripts, tools, plugins, and dashboards make Wikipedia more efficient for those who know how to work with them, but like all organizational culture, newcomers must learn them if they want to fully participate. I illustrate how cultural and organizational expertise is enacted around algorithmic agents by discussing two autoethnographic vignettes, which relate my personal experience as a veteran in Wikipedia. I present thick descriptions of how governance and gatekeeping practices are articulated through and in alignment with these automated infrastructures. Over the past 15 years, Wikipedian veterans and administrators have made specific decisions to support administrative and editorial workflows with automation in particular ways and not others. I use these cases of Wikipedia's bot-supported bureaucracy to discuss several issues in the fields of critical algorithms studies, critical data studies, and fairness, accountability, and transparency in machine learning -- most principally arguing that scholarship and practice must go beyond trying to "open up the black box" of such systems and also examine sociocultural processes like newcomer socialization.Comment: 14 pages, typo fixed in v

A Case for Machine Ethics in Modeling Human-Level Intelligent Agents

This paper focuses on the research field of machine ethics and how it relates to a technological singularity—a hypothesized, futuristic event where artificial machines will have greater-than-human-level intelligence. One problem related to the singularity centers on the issue of whether human values and norms would survive such an event. To somehow ensure this, a number of artificial intelligence researchers have opted to focus on the development of artificial moral agents, which refers to machines capable of moral reasoning, judgment, and decision-making. To date, different frameworks on how to arrive at these agents have been put forward. However, there seems to be no hard consensus as to which framework would likely yield a positive result. With the body of work that they have contributed in the study of moral agency, philosophers may contribute to the growing literature on artificial moral agency. While doing so, they could also think about how the said concept could affect other important philosophical concepts

Robot Consciousness: Physics and Metaphysics Here and Abroad

Interest has been renewed in the study of consciousness, both theoretical and applied, following developments in 20th and early 21st-century logic, metamathematics, computer science, and the brain sciences. In this evolving narrative, I explore several theoretical questions about the types of artificial intelligence and offer several conjectures about how they affect possible future developments in this exceptionally transformative field of research. I also address the practical significance of the advances in artificial intelligence in view of the cautions issued by prominent scientists, politicians, and ethicists about the possible dangers of such sufficiently advanced general intelligence, including by implication the search for extraterrestrial intelligence

A Wikipedia Literature Review

This paper was originally designed as a literature review for a doctoral dissertation focusing on Wikipedia. This exposition gives the structure of Wikipedia and the latest trends in Wikipedia research