Application of the Optimized Baxter Model to the hard-core attractive Yukawa system

We perform Monte Carlo simulations on the hard-core attractive Yukawa system to test the Optimized Baxter Model that was introduced in [P.Prinsen and T. Odijk, J. Chem. Phys. 121, p.6525 (2004)] to study a fluid phase of spherical particles interacting through a short-range pair potential. We compare the chemical potentials and pressures from the simulations with analytical predictions from the Optimized Baxter Model. We show that the model is accurate to within 10 percent over a range of volume fractions from 0.1 to 0.4, interaction strengths up to three times the thermal energy and interaction ranges from 6 to 20 % of the particle diameter, and performs even better in most cases. We furthermore establish the consistency of the model by showing that the thermodynamic properties of the Yukawa fluid computed via simulations may be understood on the basis of one similarity variable, the stickiness parameter defined within the Optimized Baxter Model. Finally we show that the Optimized Baxter Model works significantly better than an often used, naive method determining the stickiness parameter by equating the respective second virial coefficients based on the attractive Yukawa and Baxter potentials.Comment: 11 pages, 8 figure

RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation

In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation. Unlike image data which contain spatial correlations, a user-item interaction matrix, commonly utilized in recommendation, lacks spatial relationships between users and items. We formulate diffusion on a 1D vector and propose binomial diffusion, which explicitly models binary user-item interactions with a Bernoulli process. We show that RecFusion approaches the performance of complex VAE baselines on the core recommendation setting (top-n recommendation for binary non-sequential feedback) and the most common datasets (MovieLens and Netflix). Our proposed diffusion models that are specialized for 1D and/or binary setups have implications beyond recommendation systems, such as in the medical domain with MRI and CT scans.Comment: code: https://github.com/gabriben/recfusio

Sustainability and Genericity of CLARIN Services in the Netherlands

Based on the ten years that have elapsed since the start of the CLARIN- NL project and its follow-up CLARIAH-NL, this chapter offers an analysis of the sustainability and genericity of services created in the context of CLARIN in the Netherlands. Our focus is on search applications, for which we make a proposal for coming to a more efficient and sustainable approach not only in the Netherlands but also CLARIN-wide. We also offer a number of general recommendations for improving sustainability of infrastructure services

Feeding the Second Screen: Semantic Linking based on Subtitles

Television is changing. Increasingly, broadcasts are consumed interactively. This allows broadcasters to provide consumers with additional background information that they may bookmark for later consumption. To support this type of functionality, we consider the task of linking a textual streams derived from live broadcasts to Wikipedia. While link generation has received considerable attention in recent years, our task has unique demands that require an approach that needs to (i) be high-precision oriented, (ii) perform in real-time, (iii) work in a streaming setting, and (iv) typically, with a very limited context. We propose a learning to rerank approach that significantly improves over a strong baseline in terms of effectiveness and whose processing time is very short. We extend this approach, leveraging the streaming nature of the textual sources that we link by modeling context as a graph. We show how our graph-based context model further improves effectiveness. For evaluation purposes we create a dataset of segments of television subtitles that we make available to the research community

Exploring Entity Associations Over Time

We address the problem of entity-oriented search in the humanities and social sciences domain. We are particularly interested in retrieving entities related to a query entity and finding associations between these entities over time. Evidence from our target end users suggests that it is more informative to view these associations as dynamic phenomena that evolve over time than as static phenomena. We present work-in-progress on methods to extract these associations and their temporal extent, and discuss a way of presenting them in an exploratory search interface. This interface is intended to help users to discover interesting associations between entities over time

Feeding the Second Screen: Semantic Linking based on Subtitles (Abstract) ∗

Television broadcasts are increasingly consumed on an interactive device or with such a device in the vicinity. Around 70 % of tablet and smartphone owners use their devices while watching television [11]. This allows broadcasters to provide consumers with additional background information that they may bookmark for later consumption in applications such as depicted in Figure 1. For live television, edited broadcast-specific content to be used on second screens is hard to prepare in advance. We present an approach for automatically generating links to background information in real-time, to be used on second screens. We base our semantic linking approach for television broadcasts on subtitles and Wikipedia, thereby effectively casting the task as one of identifying and generating links for elements in the stream of subtitles. The process of automatically generating links to Wikipedia i