561 research outputs found
Trust- and Distrust-Based Recommendations for Controversial Reviews
Recommender systems that incorporate a social trust network among their users have the potential to make more personalized recommendations compared to traditional collaborative ïŹltering systems, provided they succeed in utilizing the additional trust and distrust information to their advantage. We compare the performance of several well-known trust-enhanced techniques for recommending controversial reviews from Epinions.com, and provide the ïŹrst experimental study of using distrust in the recommendation process
Extending boolean regulatory network models with answer set programming
Because of their simplicity, boolean networks are a popular formalism to model gene regulatory networks. However, they have their limitations, including their inability to formally and unambiguously define network behaviour, and their lack of the possibility to model meta interactions, i.e., interactions that target other interactions. In this paper we develop an answer set programming (ASP) framework that supports threshold boolean network semantics and extends it with the capability to model meta interactions. The framework is easy to use but sufficiently flexible to express intricate interactions that go beyond threshold network semantics as we illustrate with an example of a Mammalian cell cycle network. Moreover, readily available answer set solvers can be used to find the steady states of the network
Active Learning and ICT in TEM
The University of Twente is a young and dynamic research university in the Netherlands where the development of new and relevant technological knowledge is at the forefront in research and education. The UT radically redesigned all the bachelorâs programmes in the academic year 2013-2014. All new bachelorâs programmes are designed according to our own Twente Educational Model (TEM). The TEM principles are (1) modular education, (2) active learning - project based work, (3) personal responsibility, (4) learning together and (5) quick and correct fit to get students in the most suitable degree programme. In the last two years several pilots focusing on active learning and ICT have been carried out within the TEM curriculum. These pilots include a peer feedback project, a peer instruction project and a digital portfolio system. All pilots are done in collaboration with faculty staff. They supply useful information for other Faculties. In this paper we focus in particular on peer feedback
Multiple Records of Monoecy in Dioecious Taxa of Hawaiian Coprosma spp. (Rubiaceae).
The breeding systems of the 110+ species of Coprosma J.R. Forst. & G. Forst. across the Pacific are largely considered dioecious, with male and female flowers occurring on separate plants (oliver 1935). However, for many species, particularly of New Zealand, the dioecious breeding system is leaky. Coprosma species exhibiting leaky dioecy are primarily dioecious, with male and female flowers on separate plants, but individuals occasionally develop apparently functional bisexual flowers, which sporadically occur among an abundance of unisexual flowers. A putative monoecious Coprosma taxon was once reported for the Macquarie Island individuals of C. perpusilla Colenso (= C. pumila Hook.f.), but later dispelled as being dioecious (lloyd & Horning 1979).
In March 2016, the first author of this paper embarked on an archipelago-wide tripof the Hawaiian Islands aiming to collect and observe multiple populations of all endemic Hawaiian species of Coprosma (Rubiaceae). As a result, four confirmed cases of monoecious individuals were documented for Hawaiian Coprosma for the first time. Three additional instances may represent either monoecious or leaky dioecious observations. The collection results are detailed below. All specimens are deposited at BISH and duplicates were either sent to PTBG or US herbaria. Figure 1 depicts photos of monoecious individuals collected in the field
Computing fuzzy rough approximations in large scale information systems
Rough set theory is a popular and powerful machine learning tool. It is especially suitable for dealing with information systems that exhibit inconsistencies, i.e. objects that have the same values for the conditional attributes but a different value for the decision attribute. In line with the emerging granular computing paradigm, rough set theory groups objects together based on the indiscernibility of their attribute values. Fuzzy rough set theory extends rough set theory to data with continuous attributes, and detects degrees of inconsistency in the data. Key to this is turning the indiscernibility relation into a gradual relation, acknowledging that objects can be similar to a certain extent. In very large datasets with millions of objects, computing the gradual indiscernibility relation (or in other words, the soft granules) is very demanding, both in terms of runtime and in terms of memory. It is however required for the computation of the lower and upper approximations of concepts in the fuzzy rough set analysis pipeline. Current non-distributed implementations in R are limited by memory capacity. For example, we found that a state of the art non-distributed implementation in R could not handle 30,000 rows and 10 attributes on a node with 62GB of memory. This is clearly insufficient to scale fuzzy rough set analysis to massive datasets. In this paper we present a parallel and distributed solution based on Message Passing Interface (MPI) to compute fuzzy rough approximations in very large information systems. Our results show that our parallel approach scales with problem size to information systems with millions of objects. To the best of our knowledge, no other parallel and distributed solutions have been proposed so far in the literature for this problem
Excel
Les TIC au primaire vous le dĂ©montre. Ce manuel propose aussi des ateliers pour amĂ©liorer ses connaissances technologiques et plusieurs applications sur la façon dâenseigner et sur lâĂ©valuation des Ă©lĂšves.
Cet ouvrage collectif de 8 auteurs dâuniversitĂ©s quĂ©bĂ©coises et canadiennes permettra Ă lâenseignant de dĂ©couvrir lâimportance de lâutilisation des technologies dans la rĂ©ussite des Ă©lĂšves.
Extract taken from publisher\u27s website
ISBN: 978-2-7617-2767-
Internet
Les TIC au primaire vous le dĂ©montre. Ce manuel propose aussi des ateliers pour amĂ©liorer ses connaissances technologiques et plusieurs applications sur la façon dâenseigner et sur lâĂ©valuation des Ă©lĂšves.
Cet ouvrage collectif de 8 auteurs dâuniversitĂ©s quĂ©bĂ©coises et canadiennes permettra Ă lâenseignant de dĂ©couvrir lâimportance de lâutilisation des technologies dans la rĂ©ussite des Ă©lĂšves.
Extract taken from publisher\u27s website
ISBN: 978-2-7617-2767-
Efficient Solving of Time-dependent Answer Set Programs
Answer set programs with time predicates are useful to model systems whose properties depend on time, like for example gene regulatory networks. A state of such a system at time point t then corresponds to the literals of an answer set that are grounded with time constant t. An important task when modelling time-dependent systems is to find steady states from which the system\u27s behaviour does not change anymore. This task is complicated by the fact that it is typically not known in advance at what time steps these steady states occur. A brute force approach of estimating a time upper bound tmax and grounding and solving the program w.r.t. that upper bound leads to a suboptimal solving time when the estimate is too low or too high. In this paper we propose a more efficient algorithm for solving Markovian programs, which are time-dependent programs for which the next state depends only on the previous state. Instead of solving these Markovian programs for a long time interval {0,...,tmax}, we successively find answer sets of parts of the grounded program. Our approach guarantees the discovery of all steady states and cycles while avoiding unnecessary extra work
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