The suitability of peer-to-peer (P2P) approaches for full-text Web retrieval has recently been questioned because the claimed unacceptable bandwidth consumption induced by from very large document collections. In this contribution we formalize a novel indexing/retrieval model that achieves high performance, cost-efficient indexing with highly discriminative keys (HDKs) stored in distributed global index maintained structured P2P network. HDKs correspond to carefully selected terms and term...

In this paper, we present a query-driven indexing/retrieval strategy for efficient full text retrieval from large document collections distributed within structured P2P network. Our indexing is based on two important properties: (1) the generated index stores posting lists carefully chosen term combinations, and (2) containing too many references are truncated to bounded number of their top-ranked elements. These properties guarantee acceptable storage bandwidth requirements, essentially...

We present Alvis peers, a full-text P2P retrieval engine designed to offer performance comparable centralized solutions while scaling very large number of peers. It is the result our research efforts within project Alvis1 European FP 6 STREP ALVIS, http://www.alvis.info/ that aims at building truly-distributed semantic search engine. To cope with problem unscalable bandwidth consumption in network, implements novel model indexes highly-discriminative keys (HDKs)---terms and term sets...

We present a query-driven algorithm for the distributed indexing of large document collections within structured P2P networks. To cope with bandwidth consumption that has been identified as major problem standard approach single term indexing, we leverage index stores up to top-k references only carefully chosen combinations. In addition, since number possible combinations extracted from collection can be very large, propose use query statistics such are indeed frequently requested by users....

In this paper we present the AlvisP2P IR engine, which enables efficient retrieval with multi-keyword queries from a global document collection available in P2P network. such network, each peer publishes its local index and invests part of computing resources (storage, CPU, bandwidth) to maintain fraction index. This investment is rewarded by network-wide accessibility documents via search facility. The engine uses an optimized overlay network relies on novel indexing/retrieval mechanisms...

Abstract During the early stages of Industry 4.0 era, teleoperation with human involvement in manufacturing processes and robot operation remained important. The existing technologies have limitations providing operator spatial awareness initiative control mechanism, making their applications difficult tasks high complexity precision. This study implements advancements from Internet Things (IoT) Virtual Reality (VR) technology to improve real-time for industrial robots. proposed design...

We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as major obstacle full-text in networks, we truncate posting lists associated features to constant size storing only top-k ranked document references. compensate loss of information caused by truncation, extend set carefully chosen term sets. Indexing sets are selected based on query statistics extracted from logs,...

We present a query-driven algorithm for the distributed in- dexing of large document collections within structured P2P networks. To cope with bandwidth consumption that has been identi¯ed as major problem standard approach single term indexing, we leverage index th

In the development of digital twin systems for unmanned surface vehicles (USVs), collision classification is a fundamental feature to implement. Integrating position information into remote control significantly enhances operator situational awareness and facilitates effective motion strategies even when camera visitor compromised by challenging environmental conditions. This paper presents three-step approach employing onboard inertial measurement unit (IMU) data. first step, sensor...

Search engines essentially rely on the structure of graph hyperlinks. Although accurate for main trend, this is not effective when some query ambiguous. Leveraging semantic information by mean interest matching allows proposing complementary results that are tailored to user's expectations. This paper proposes a collaborative search companion system, CoFeed, collects user queries and considers feedback build user-centric document-centric profiling information. Over time, system constructs...

Standard general-purpose Web retrieval relies on centralized search engines that do not realistically scale when applied to the exponentially growing number of documents available Web. By taking advantage resource sharing principle, Peer-to-Peer (P2P) techniques represent a promising architectural alternative for building decentralized offering true Web-size scalability, provided enough peers are available. However, in all such P2P approaches proposed so far, excessive network bandwidth...

Despite the many research efforts invested recently in peer-to-peer search engines, none of proposed system has reached level quality and efficiency their centralized counterpart. One main reasons for this inferior performance is difficulty to attract a critical mass users that would make truly competitive. We argue decentralized mechanisms should not aim at replacing existing but instead complement them by adding novel functionalities be difficult provide manner. This paper introduces an...