A Topic Recommender for Journalists

The way in which people acquire information on events and form their own opinion on them has changed dramatically with the advent of social media. For many readers, the news gathered from online sources become an opportunity to share points of view and information within micro-blogging platforms such as Twitter, mainly aimed at satisfying their communication needs. Furthermore, the need to deepen the aspects related to news stimulates a demand for additional information which is often met through online encyclopedias, such as Wikipedia. This behaviour has also influenced the way in which journalists write their articles, requiring a careful assessment of what actually interests the readers. The goal of this paper is to present a recommender system, What to Write and Why, capable of suggesting to a journalist, for a given event, the aspects still uncovered in news articles on which the readers focus their interest. The basic idea is to characterize an event according to the echo it receives in online news sources and associate it with the corresponding readers’ communicative and informative patterns, detected through the analysis of Twitter and Wikipedia, respectively. Our methodology temporally aligns the results of this analysis and recommends the concepts that emerge as topics of interest from Twitter and Wikipedia, either not covered or poorly covered in the published news articles

How Philosophy of Mind Needs Philosophy of Chemistry

By the 1960s many (perhaps most) philosophers had adopted ‘physicalism’ ─ the view that physical causes fully account for mental activities. However, controversy persists about what count as ‘physical causes’. ‘Reductive’ physicalists recognize only microphysical (elementary-particle-level) causality. Many (perhaps most) physicalists are ‘non-reductive’ ─ they hold that entities considered by other (‘special’) sciences have causal powers. Philosophy of chemistry can help resolve main issues in philosophy of mind in three ways: developing an extended mereology applicable to chemical combination, testing whether ‘singularities’ prevent reduction of chemistry to microphysics, and demonstrating ‘downward causation’ in complex networks of chemical reactions

How Philosophy of Mind Needs Philosophy of Chemistry

By the 1960s many (perhaps most) philosophers had adopted ‘physicalism’ ─ the view that physical causes fully account for mental activities. However, controversy persists about what count as ‘physical causes’. ‘Reductive’ physicalists recognize only microphysical (elementary-particle-level) causality. Many (perhaps most) physicalists are ‘non-reductive’ ─ they hold that entities considered by other (‘special’) sciences have causal powers. Philosophy of chemistry can help resolve main issues in philosophy of mind in three ways: developing an extended mereology applicable to chemical combination, testing whether ‘singularities’ prevent reduction of chemistry to microphysics, and demonstrating ‘downward causation’ in complex networks of chemical reactions

PaperRobot: Incremental Draft Generation of Scientific Ideas

We present a PaperRobot who performs as an automatic research assistant by (1) conducting deep understanding of a large collection of human-written papers in a target domain and constructing comprehensive background knowledge graphs (KGs); (2) creating new ideas by predicting links from the background KGs, by combining graph attention and contextual text attention; (3) incrementally writing some key elements of a new paper based on memory-attention networks: from the input title along with predicted related entities to generate a paper abstract, from the abstract to generate conclusion and future work, and finally from future work to generate a title for a follow-on paper. Turing Tests, where a biomedical domain expert is asked to compare a system output and a human-authored string, show PaperRobot generated abstracts, conclusion and future work sections, and new titles are chosen over human-written ones up to 30%, 24% and 12% of the time, respectively.Comment: 12 pages. Accepted by ACL 2019 Code and resource is available at https://github.com/EagleW/PaperRobo

Production structure and economic fluctuations

We aim at contributing to the debate on the mechanisms and properties of economic fluctuations. We consider a crucial aspect among many thought to influence this ubiquitous and extremely relevant phenomenon: the interaction structure that characterises the organisation of production, that is, the production relation among sectors of a system. We build — and simulate — a very simple model representing an input–output system where sectors/firms adapt production and desired levels of stocks. Their output serves both an exogenous final demand and the intermediate demand solicited by the other sectors of the system. Series of simulation runs allow to derive relevant and non–obvious conclusions concerning the levels and, more importantly, the volatility of economic activity, as an outcome of the same, inherent, economic structure. We claim that the results that we obtain through the highly abstract representation we use, provide useful intuitions on the working of economic cycles, to be later integrated by further studies. As a by–product of our analysis, we also suggest that the methodology we adopt can provide valuable insights by allowing a detailed analysis of the time path generated in the artificial systems, and there- fore assessing with precisions the same mechanisms that affect real–world systems. The natural following step, left for further research, is to investigate how those mechanisms are empirically generated

Merleau-Ponty’s implicit critique of the new mechanists

I argue (1) that what (ontic) New Mechanistic philosophers of science call mechanisms would be material Gestalten, and (2) that Merleau-Ponty’s engagement with Gestalt theory can help us frame a standing challenge against ontic conceptions of mechanisms. In short, until the (ontic) New Mechanist can provide us with a plausible account of the organization of mechanisms as an objective feature of mind-independent ontic structures in the world which we might discover – and no ontic Mechanist has done so – it is more conservative to claim that mechanistic organization is instead a mind-dependent aspect of our epistemic strategies of mechanistic explanation

Negative Statements Considered Useful

Knowledge bases (KBs), pragmatic collections of knowledge about notable entities, are an important asset in applications such as search, question answering and dialogue. Rooted in a long tradition in knowledge representation, all popular KBs only store positive information, while they abstain from taking any stance towards statements not contained in them. In this paper, we make the case for explicitly stating interesting statements which are not true. Negative statements would be important to overcome current limitations of question answering, yet due to their potential abundance, any effort towards compiling them needs a tight coupling with ranking. We introduce two approaches towards compiling negative statements. (i) In peer-based statistical inferences, we compare entities with highly related entities in order to derive potential negative statements, which we then rank using supervised and unsupervised features. (ii) In query-log-based text extraction, we use a pattern-based approach for harvesting search engine query logs. Experimental results show that both approaches hold promising and complementary potential. Along with this paper, we publish the first datasets on interesting negative information, containing over 1.1M statements for 100K popular Wikidata entities

Being Emergence vs. Pattern Emergence: Complexity, Control, and Goal-Directedness in Biological Systems

Emergence is much discussed by both philosophers and scientists. But, as noted by Mitchell (2012), there is a significant gulf; philosophers and scientists talk past each other. We contend that this is because philosophers and scientists typically mean different things by emergence, leading us to distinguish being emergence and pattern emergence. While related to distinctions offered by others between, for example, strong/weak emergence or epistemic/ontological emergence (Clayton, 2004, pp. 9–11), we argue that the being vs. pattern distinction better captures what the two groups are addressing. In identifying pattern emergence as the central concern of scientists, however, we do not mean that pattern emergence is of no interest to philosophers. Rather, we argue that philosophers should attend to, and even contribute to, discussions of pattern emergence. But it is important that this discussion be distinguished, not conflated, with discussions of being emergence. In the following section we explicate the notion of being emergence and show how it has been the focus of many philosophical discussions, historical and contemporary. In section 3 we turn to pattern emergence, briefly presenting a few of the ways it figures in the discussions of scientists (and philosophers of science who contribute to these discussions in science). Finally, in sections 4 and 5, we consider the relevance of pattern emergence to several central topics in philosophy of biology: the emergence of complexity, of control, and of goal-directedness in biological systems