The availability of the sheer volume Copernicus Sentinel-2 imagery has created new opportunities for exploiting deep learning methods land use cover (LULC) image classification at large scales. However, an extensive set benchmark experiments is currently lacking, i.e. models tested on same dataset, with a common and consistent metrics, in hardware. In this work, we BigEarthNet multispectral dataset to first time different state-of-the-art multi-label, multi-class LULC problem, contributing...

In today’s world, technology has become deep-rooted and more accessible than ever over a plethora of different devices platforms, ranging from company servers commodity PCs to mobile phones wearables, interconnecting wide range stakeholders such as households, organizations critical infrastructures. The sheer volume variety the operating systems, device particularities, various usage domains accessibility-ready nature platforms creates vast complex threat landscape that is difficult contain....

This work investigates the ability of open Large Language Models (LLMs) to predict citation intent through in-context learning and fine-tuning. Unlike traditional approaches that rely on pre-trained models like SciBERT, which require extensive domain-specific pretraining specialized architectures, we demonstrate general-purpose LLMs can be adapted this task with minimal task-specific data. We evaluate twelve model variations across five prominent LLM families using zero, one, few, many-shot...

Today, more than ever, the popularity of decentralized payment systems has risen, creating an outbreak new cryptocurrencies hitting market. Unique websites have been staged for each cryptocurrency, where information and means mining are available daily. People visit those cryptocurrency either from desktop or mobile devices. Thus, impulsion appropriate promotion customer factors affecting it rises. The above process increases organizations’ website visibility, raising need relationships...

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We study the problem of offering publish/subscribe functionality on top structured overlay networks using data models and languages from IR. show how to achieve this by extending distributed hash table Chord present a detailed experimental evaluation our proposals.

In the information filtering paradigm, clients subscribe to a server with continuous queries or profiles that express their needs. Clients can also publish documents servers. Whenever document is published, satisfying this are found and notifications sent appropriate clients. This article deals problem needs be solved efficiently by each server: Given database of db d , find all q ∈ match . We present data structures indexing algorithms enable us solve for large databases expressed in model...

Privacy of Internet users is at stake because they expose personal information in posts created online communities, search queries, and other activities. An adversary that monitors a community may identify the with most sensitive properties utilize this knowledge against them (e.g., by adjusting pricing goods or targeting ads nature). Existing privacy models for structured data are inadequate to capture risks from user posts.

We study the problem of selective dissemination information in P2P networks. present our work on data models and laiguages for textual discuss a relemnt architecture that motivates efforts. also survey results computational complexity three related algorithmic problems (query satisfiability, entailment filtering) efficient algorithms most crucial these (filtering). Finally, we features P2P-DIET, super-peer system have implemented at Technical Lniversity Crete, realizes vision is able to...

Publishing data about individuals, in a privacy-preserving way, has led to large body of research. Meanwhile, algorithms for anonymizing datasets, with relational or transaction attributes, that preserve truthfulness, have attracted significant interest from organizations. However, selecting the most appropriate algorithm is still far trivial, and tools assist publishers this task are needed. In response, we develop SECRETA, system analyzing effectiveness efficiency anonymization algorithms....

Advancements in cultural informatics have significantly influenced the way we perceive, analyze, communicate and understand culture. New data sources, such as social media, digitized content, Internet of Things (IoT) devices, allowed us to enrich customize experience, but at same time created an avalanche new that needs be stored appropriately managed order value. Although management plays a central role driving forward heritage domain, solutions applied so far are fragmented, physically...

In the selective dissemination of information (or publish/subscribe) paradigm, clients subscribe to a server with continuous queries profiles) that express their needs. Clients can also publish documents servers. Whenever document is published, satisfying this are found and notifications sent appropriate clients. This paper deals filtering problem needs be solved effciently by each server: Given database db d, find all q ∈ match d. We present data structures indexing algorithms enable us...

Semantic overlay networks cluster peers that are semantically, thematically or socially close into groups, by means of a rewiring procedure is periodically executed each peer. This establishes new connections to similar and disregards dissimilar. Retrieval effectiveness then improved exploiting this information at query time (as queries may address clusters peers). Although all systems based on semantic apply some technique, there no comprehensive study showing the effect system’s...

We study the problem of continuous relational query processing in Internet-scale overlay networks realized by distributed hash tables. concentrate on case two-way equi-join queries. Joins are hard to evaluate a environment because data from more than one relations is needed, and this inserted network asynchronously. Each time new tuple inserted, nodes have cooperate check if can contribute satisfaction when combined with previously tuples. propose series algorithms that initially index...

Information filtering, also referred to as publish/subscribe, complements one-time searching since users are able subscribe information sources and be notified whenever new documents of interest published. In approximate filtering only selected sources, that likely publish relevant the user interests in future, monitored. To achieve this functionality, a subscriber exploits statistical metadata identify promising publishers index its continuous query those publishers. The statistics...

Content providers are naturally distributed and produce large amounts of new information every day. Peer-to-peer filtering is a promising approach that offers scalability, adaptivity to high dynamics, failure resilience. The authors developed two approaches utilize the chord hash table as routing substrate, but one stresses retrieval effectiveness, whereas other relaxes recall guarantees achieve lower message traffic thus better scalability. This article highlights approaches' main...

The World Wide Web has become a key source of knowledge pertaining to almost every walk life. Unfortunately, much data on the is highly ephemeral in nature, with more than 50-80% content estimated be changing within short time. Continuing pioneering efforts many national (digital) libraries, organizations such as International Internet Preservation Consortium (IIPC), Archive (IA) and European (EA) have been tirelessly working towards preserving ever Web.

The clear, social, and dark web have lately been identified as rich sources of valuable cyber-security information that -given the appropriate tools methods-may be identified, crawled subsequently leveraged to actionable cyber-threat intelligence. In this work, we focus on gathering task, present a novel crawling architecture for transparently harvesting data from security websites in clear web, forums social hacker forums/marketplaces web. proposed adopts two-phase approach harvesting....