Prior Knowledge-Based Event Network for Chinese Text

Text representation is a basic issue of text information processing and event plays an important role in text understanding; both attract the attention of scholars. The event network conceals lexical relations in events, and its edges express logical relations between events in document. However, the events and relations are extracted from event-annotated text, which makes it hard for large-scale text automatic processing. In the paper, with expanded CEC (Chinese Event Corpus) as data source, prior knowledge of manifestation rules of event and relation as the guide, we propose an event extraction method based on knowledge-based rule of event manifestation, to achieve automatic building and improve text processing performance of event network

Comparing Weblogs to Threaded Discussion Tools in Online Educational Contexts.

Weblogs or blogs are being heralded as the “next big thing” in education. In this article we examine the advantages and disadvantages of this form of Internet-based interaction using the Community of Inquiry model with its focus on social, cognitive and teaching presences. We conclude that blogging has distinct advantages over more common threaded discussion in its support of style, ownership and identity, and its public nature may enhance resolution phases of cognitive presence. However, its lack of safety and the current inefficiencies of linking and threading messages present greater challenges than the more familiar threaded discussion or email list. Perhaps the blog’s greatest relative advantage is for non formal and open education that takes learning beyond the traditional course

Hierarchical categorisation of web tags for Delicious

In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. The benefits of social tagging are clear – tags enhance Web content browsing and search. However, since these tags may be publicly available to any Internet user, a privacy attacker may collect this information and extract an accurate snapshot of users’ interests or user profiles, containing sensitive information, such as health-related information, political preferences, salary or religion. In order to hinder attackers in their efforts to profile users, this report focuses on the practical aspects of capturing user interests from their tagging activity. More accurately, we study how to categorise a collection of tags posted by users in one of the most popular bookmarking services, Delicious (http://delicious.com).Preprin

Multi-facet rating of online hotel reviews: issues, methods and experiments

Online product reviews are becoming increasingly popular, and are being used more and more frequently by consumers in order to choose among competing products. Tools that rank competing products in terms of the satisfaction of consumers that have purchased the product before, are thus also becoming popular. We tackle the problem of rating (i.e., attributing a numerical score of satisfaction to) consumer reviews based on their tex- tual content. In this work we focus on multi-facet rating of hotel reviews, i.e., on the case in which the review of a hotel must be rated several times, according to several aspects (e.g., cleanliness, dining facilities, centrality of location). We explore several aspects of the problem, including the vectorial representation of the text based on sentiment analysis, collocation analysis, and feature selection for ordinal-regression learning. We present the results of experiments conducted on a corpus of approximately 15,000 hotel reviews that we have crawled from a popular hotel review site

Discourse-centric learning analytics: mapping the terrain

There is an increasing interest in developing learning analytic techniques for the analysis, and support of, high quality learning discourse. This paper maps the terrain of discourse-centric learning analytics (DCLA), outlining the distinctive contribution of DCLA and outlining a definition for the field moving forwards. It is our claim that DCLA provide the opportunity to explore the ways in which: discourse of various forms both resources and evidences learning; the ways in which small and large groups, and individuals make and share meaning together through their language use; and the particular types of language – from discipline specific, to argumentative and socio-emotional – associated with positive learning outcomes. DCLA is thus not merely a computational aid to help detect or evidence ‘good’ and ‘bad’ performance (the focus of many kinds of analytic), but a tool to help investigate questions of interest to researchers, practitioners, and ultimately learners. The paper ends with three core issues for DCLA researchers – the challenge of context in relation to DCLA; the various systems required for DCLA to be effective; and the means through which DCLA might be delivered for maximum impact at the micro (e.g. learner), meso (e.g. school), and macro (e.g. governmental) levels

Discourse-centric learning analytics

Drawing on sociocultural discourse analysis and argumentation theory, we motivate a focus on learners' discourse as a promising site for identifying patterns of activity which correspond to meaningful learning and knowledge construction. However, software platforms must gain access to qualitative information about the rhetorical dimensions to discourse contributions to enable such analytics. This is difficult to extract from naturally occurring text, but the emergence of more-structured annotation and deliberation platforms for learning makes such information available. Using the Cohere web application as a research vehicle, we present examples of analytics at the level of individual learners and groups, showing conceptual and social network patterns, which we propose as indicators of meaningful learning

DDoS hive comb: An IP stresser made by the community

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: Raúl Roca Cánovas[en] Denial of service attacks (or DoS attacks) consist of attacking a service on a server in order to temporarily interrupt the services of the host connected to the Internet. There are a wide variety of techniques and strategies that can be used to achieve this goal. This work aims to help these victims by creating an IP Stresser that allows the simulation of various DoS attacks. In this way, victims can check the stress capacity that their teams can handle and adapt different mitigation plans in various types of circumstances. The IP Stresser that will be developed in this project consists of a website accessible to everyone for free. The idea of this website is to try to create a community where with the help of other users a botnet can be created by means of a script that can be downloaded from this same website. Although this work is more focused on the practical part, we will try to explain briefly the structure of the Internet and how these attacks act and influence society

Plasmonic Oligomers with Tunable Conductive Nanojunctions

International audienceEngineering plasmonic hot-spots is essential for applications of plasmonic nanoparticles. A particularly appealing route is to weld plasmonic nanoparticles together to form more complex structures sustaining plasmons with symmetries targeted to given applications. However, thecontrol of the welding and subsequent hotspot characteristic is still challenging. Herein, we demonstrate an original method that connects gold particles to their neighbors by another metal of choice. We first assemble gold bipyramids in a tip-to-tip configuration, yielding short chainsof variable length and grow metallic junctions in a second step. We follow the chain formation and the deposition of the second metal (i.e. silver or palladium) via UV/Vis spectroscopy and we map the plasmonic properties using electron energy loss spectroscopy. The formation ofsilver bridges leads to a huge redshift of the longitudinal plasmon modes into the mid-infrared region, while the addition of palladium results in a redshift accompanied by significant plasmon damping

How content contributors assess and establish credibility on the web

The proliferation of user‐generated content (UGC) is one of the distinguishing characteristics of Web 2.0. Internet users contribute content online through platforms such as blogs, wikis, video sharing sites, and sites that allow user feedback. Yet little is known of the credibility practices of these content contributors. Through phone interviews conducted with 29 online content contributors, this study investigates how content contributors assess credibility when gathering information for their online content creation and mediation activities, as well as the strategies they use to establish the credibility of the content they create. These contributors reported that they engaged in content creation activities such as posting or commenting on blogs or online forums, rating or voting on online content, and uploading photos, music, or video. We found that credibility judgments made when gathering information for online content creation and mediation activities could be grouped into three levels: intuitive, heuristic, and strategy‐based. We identified three distinctive ways of establishing credibility that are applied during different phases of content contribution: ensuring credibility during the content creation phase; signaling credibility during the content presentation phase; and reinforcing credibility during the post‐production phase. We also discovered that content contributors tend to carry over the strategies they used for assessing credibility during information gathering to their strategies for establishing the credibility of their own content. Theoretical implications for credibility research and practical implications for developing information literacy programs are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90253/1/14504801163_ftp.pd