A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.

The fossil calibration database - A new resource for divergence dating

Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important, and often least appreciated, step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for non-specialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as one key pipeline for peer-reviewed calibrations to enter the database.

Griggs' Folly: An Essay on the Theory, Problems, and Origin of the Adverse Impact Definition of Employment Discrimination and a Recommendation for Reform

This Article examines the adverse impact theory of employment discrimination under Title VII. The author begins by discussing the development of adverse impact in the case law, and by scrutinizing its theoretical underpinnings. He demonstrates that Congress did not intend to mandate adoption of adverse impact theory when it established Title VII. The author then argues that the Courts have exceeded their authority under Title VII by embracing the theory of adverse impact. He concludes that the courts should therefore return to a narrower theory of employment discrimination, namely, a theory based on the legal concept of “intent.”

Letter of recommendation for Jacques Judah Lyons from Isaac Leeser

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Recommendation of Jacques Judah Lyons from Surinam

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Recommendation of Multimedia Objects Using Metadata and Link Analysis

We investigate methods for recommending multimedia items suitable for an online multimedia sharing community and introduce a novel algorithm called UserRank for ranking multimedia items based on link analysis. We also take the initiative of applying EigenRumor from the domain of blogosphere to multimedia. Furthermore, we present a strategy for making personalized recommendation that combines UserRank with collaborative filtering. We evaluate our method with an informal user study and show that results obtained are promising.

Dressing up Tinderella: Interrogating authenticity claims on the mobile dating app Tinder

Mobile dating applications (‘apps’) have increased in popularity over recent years, with Tinder among the first to break into the mainstream heterosexual market. Since mobile dating intensifies the need to confirm that potential dates are not misrepresenting themselves and are safe to meet in person, Tinder’s success indicates that it has allayed these concerns regarding the authenticity of its users. This article combines Giddens’ conceptualization of authenticity, as the ability to reference a coherent biographical narrative, with Callon’s sociology of translation to investigate Tinder’s framing of authenticity within mobile dating. Applying a walkthrough method that interrogates Tinder’s technological architecture, promotional materials, and related media, this hybrid theoretical framework is used to identify how Tinder configures an actor-network that establishes its app as the solution to users’ concerns, enrols individuals in using its features in authenticity claims, and popularizes Tinder’s framing across public discourse. This network of human and non-human actors frames authenticity as being established through one’s Facebook profile and adherence to normative standards relating to age, gender, ethnicity, and socioeconomic status. However, user discourses on other social media identify and challenge negative outcomes of this framing, with normativity fostering discrimination and Facebook verification failing to prevent abusive behavior. This case study of Tinder paves the way for future investigation into user responses to its framing. Further, it demonstrates the efficacy and broader applicability of this theoretical approach for identifying both human and technological influences on the construction of authenticity with digital media.

Mobile Dating and Hookup App Culture

This chapter surveys the landscape of mobile dating and hookup apps—understood as media technologies, as businesses, and as sites of social practice. It situates the discussion within the broader contexts of technologically mediated dating and digital sexual cultures. By outlining a number of methodological approaches and data sources that can be used in the study of dating and hookup apps, it equips the reader with tools and approaches for investigating hookup app culture in ways that go beyond “media panics” – the familiar combination of moral panics and media effects which is so prevalent in discussions of sexuality in digital media.

Geomolecular dating and the origin of placental mammals

In modern evolutionary divergence analysis the role of geological information extends beyond providing a timescale, to informing molecular rate variation across the tree. Here I consider the implications of this development. I use fossil calibrations to test the accuracy of models of molecular rate evolution for placental mammals, and reveal substantial misspecification associated with life history rate correlates. Adding further calibrations to reduce dating errors at specific nodes unfortunately tends to transfer underlying rate errors to adjacent branches. Thus, tight calibration across the tree is vital to buffer against rate model errors. I argue that this must include allowing maximum bounds to be tight when good fossil records permit, otherwise divergences deep in the tree will tend to be inflated by the interaction of rate errors and asymmetric confidence in minimum and maximum bounds. In the case of placental mammals I sought to reduce the potential for transferring calibration and rate model errors across the tree by focusing on well-supported calibrations with appropriately conservative maximum bounds. The resulting divergence estimates are younger than others published recently, and provide the long-anticipated molecular signature for the placental mammal radiation observed in the fossil record near the 66 Ma Cretaceous–Paleogene extinction event.

Sensitive high-resolution ion microprobe U-Pb dating of prograde and retrograde ultrahigh-temperature metamorphism as exemplified by Sri Lankan granulites

Ultrahigh-temperature (UHT) granulites of the central Highland Complex, Sri Lanka, underwent some of the highest known peak temperatures of crustal metamorphism. Zircon and monazite U-Pb systems in granulites near Kandy, the highest grade region (similar to 1050 degrees C; 0.9 GPa), preserve both a record of the timing of prograde and retrograde phases of UHT metamorphism and evidence for the ages of older protolith components. Zircon grains from a quartz-saturated granulite containing relics of the peak UHT assemblage have remnant detrital cores with dates of ca. 2.5-0.83 Ga. Date clusters of ca. 1.7 and 1.04-0.83 Ga record episodes of zircon growth in the source region of the protolith sediment. Two generations of overgrowths with contrasting Th/U record metamorphic zircon growth at 569 +/- 5 and 551 +/- 7 Ma, probably in the absence and presence of monazite, respectively. The age of coexisting metamorphic monazite (547 +/- 7 Ma) is indistinguishable from that of the younger, low-Th/U zircon overgrowths. Zircon from a quartz-undersaturated monazite-absent UHT granulite with a mainly retrograde assemblage is mostly metamorphic (551 +/- 5 Ma). The ca. 570 Ma zircon overgrowths in the quartz-saturated granulite probably record partial melting just before or at the metamorphic peak. The ca. 550 Ma zircon in both rocks, and the ca. 550 Ma monazite in the quartz-saturated sample, record post-peak isothermal decompression. A possible model for this pressure-temperature-time evolution is ultrahot collisional orogeny during the assembly of Gondwana, locally superheated by basaltic underplating, followed by fast extensional exhumation.