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Exploiting Linked Open Data for a Collaborative Filtering Recommendation System

2023 | Americas Conference on Information Systems | Citations: 0
Authors: de Souza, Paulo; Durao, Frederico; Almeida, João Paulo Dias de; Mascarenhas, Ramon; Oliveira, Mayki Dos Santos

Abstract: Recommendation Systems (RS) tackle Information Overload on the web, and Collabo ... Expand

Abstract: Recommendation Systems (RS) tackle Information Overload on the web, and Collaborative Filtering (CF) is a widely used technique to estimate content relevance for users based on similar profiles. Traditional CF, however, often overlooks hidden semantic information and item relationships. This work proposes an RS that integrates Linked Open Data with CF to improve recommendation precision by leveraging semantic information about resources and their relationships. The approach calculates semantic similarity among resources using the Linked Open Data graph. By comparing error rates (MAE and RMSE) in varying scenarios, the proposed approach shows at least a 1.5% improvement in precision rates compared to traditional CF. This study contributes insights for researchers seeking to exploit Linked Open Data in recommendation contexts. Collapse

Semantic filters: DBpedia

Topics: collaborative filtering open data recommender system database system knowledge representation

Methods: computational algorithm k-nearest neighbor DBpedia experiment literature study
An Approach to Extracting Topic-guided Views from the Sources of a Data Lake
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2021 | Information Systems Frontiers | Citations: 0
Authors: Diamantini, Claudia; Lo Giudice, Paolo; Potena, Domenico; Storti, Emanuele; Ursino, Domenico

Abstract: In the last years, data lakes are emerging as an effective and an efficient supp ... Expand

Abstract: In the last years, data lakes are emerging as an effective and an efficient support for information and knowledge extraction from a huge amount of highly heterogeneous and quickly changing data sources. Data lake management requires the definition of new techniques, very different from the ones adopted for data warehouses in the past. In this scenario, one of the most challenging issues to address consists in the extraction of topic-guided (i.e., thematic) views from the (very heterogeneous and often unstructured) sources of a data lake. In this paper, we propose a new network-based model to uniformly represent structured, semi-structured and unstructured sources of a data lake. Then, we present a new approach to, at least partially, “structuring” unstructured data. Finally, we define a technique to extract topic-guided views from the sources of a data lake, based on similarity and other semantic relationships among source metadata. Collapse

Semantic filters: DBpedia

Topics: data lake knowledge representation knowledge graph Wikipedia database system

Methods: computational algorithm experiment DBpedia cluster analysis machine learning
Geo-semantic-parsing: AI-powered geoparsing by traversing semantic knowledge graphs
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2020 | Decision Support Systems | Citations: 0
Authors: Nizzoli, Leonardo; Avvenuti, Marco; Tesconi, Maurizio; Cresci, Stefano

Abstract: Online social networks convey rich information about geospatial facets of realit ... Expand

Abstract: Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus preventing its exploitation in real-time applications. We address this limitation by introducing a novel geoparsing and geotagging technique called Geo-Semantic-Parsing (GSP). GSP identifies location references in free text and extracts the corresponding geographic coordinates. To reach this goal, we employ a semantic annotator to identify relevant portions of the input text and to link them to the corresponding entity in a knowledge graph. Then, we devise and experiment with several efficient strategies for traversing the knowledge graph, thus expanding the available set of information for the geoparsing task. Finally, we exploit all available information for learning a regression model that selects the best entity with which to geotag the input text. We evaluate GSP on a well-known reference dataset including almost 10 k event-related tweets, achieving F1 = 0.66. We extensively compare our results with those of 2 baselines and 3 state-of-the-art geoparsing techniques, achieving the best performance. On the same dataset, competitors obtain F1 ≤ 0.55. We conclude by providing in-depth analyses of our results, showing that the overall superior performance of GSP is mainly due to a large improvement in recall, with respect to existing techniques. Collapse

Semantic filters: DBpedia

Topics: knowledge graph geographic information system Twitter knowledge representation decision support system

Methods: experiment computational algorithm regression analysis method DBpedia BERT
CrisMap: a Big Data Crisis Mapping System Based on Damage Detection and Geoparsing
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2018 | Information Systems Frontiers | Citations: 9
Authors: Avvenuti, Marco; Cresci, Stefano; Del Vigna, Fabio; Fagni, Tiziano; Tesconi, Maurizio

Abstract: Natural disasters, as well as human-made disasters, can have a deep impact on wi ... Expand

Abstract: Natural disasters, as well as human-made disasters, can have a deep impact on wide geographic areas, and emergency responders can benefit from the early estimation of emergency consequences. This work presents CrisMap, a Big Data crisis mapping system capable of quickly collecting and analyzing social media data. CrisMap extracts potential crisis-related actionable information from tweets by adopting a classification technique based on word embeddings and by exploiting a combination of readily-available semantic annotators to geoparse tweets. The enriched tweets are then visualized in customizable, Web-based dashboards, also leveraging ad-hoc quantitative visualizations like choropleth maps. The maps produced by our system help to estimate the impact of the emergency in its early phases, to identify areas that have been severely struck, and to acquire a greater situational awareness. We extensively benchmark the performance of our system on two Italian natural disasters by validating our maps against authoritative data. Finally, we perform a qualitative case-study on a recent devastating earthquake occurred in Central Italy. Collapse

Semantic filters: DBpedia

Topics: Twitter earthquake Wikipedia natural hazard big data

Methods: natural language processing word embedding case study support vector machine experiment
Practical parallel string matching framework for RDF entailments with GPUs
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2018 | Information Systems Frontiers | Citations: 0
Authors: Choksuchat, Chidchanok; Chantrapornchai, Chantana

Abstract: Resource Description Framework (RDF) is a commonly used format for semantic web ... Expand

Abstract: Resource Description Framework (RDF) is a commonly used format for semantic web processing. It basically contains strings representing items and their relationships which can be queried or inferred. In this paper, we propose a framework for processing large RDF data sets. It is based on Brute-force string matching on GPUs (BFG). Graphics Processing Units (GPUs) are used as a parallel platform that allows thousands of threads to find RDF data. Our search algorithm is customized to suit the nature of RDF processing and GPU memory architecture. Then, the algorithm is integrated into the proposed framework for computing queries and chaining rules for RDF data. Experiments show that utilizing these algorithms can achieve the speedup of 7 times for querying and for forward chaining compared to using the sequential version. The proposed framework can achieve a string comparison rate of 67,000 comparisons per second using 2 GPUs. Collapse

Semantic filters: DBpedia

Topics: knowledge representation computer hardware Linux parallel computing MapReduce

Methods: computational algorithm experiment DBpedia literature study design artifact
Dependency modelling for inconsistency management in Digital Preservation – The PERICLES approach
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2018 | Information Systems Frontiers | Citations: 0
Authors: Lagos, Nikolaos; Riga, Marina; Mitzias, Panagiotis; Vion-Dury, Jean-Yves; Kontopoulos, Efstratios; Waddington, Simon; Laurenson, Pip; Meditskos, Georgios; Kompatsiaris, Ioannis

Abstract: The rise of the Semantic Web has provided cultural heritage researchers and prac ... Expand

Abstract: The rise of the Semantic Web has provided cultural heritage researchers and practitioners with several tools for providing semantically rich representations and interoperability of cultural heritage collections. Although indeed offering a lot of advantages, these tools, which come mostly in the form of ontologies and related vocabularies, do not provide a conceptual model for capturing contextual and environmental dependencies, contributing to long-term digital preservation. This paper presents one of the key outcomes of the PERICLES FP7 project, the Linked Resource Model, for modelling dependencies as a set of evolving linked resources. The adoption of the proposed model and the consistency of its representation are evaluated via a specific instantiation involving the domain of digital video art. Collapse

Semantic filters: DBpedia

Topics: knowledge representation digital ecosystem semantic web

Methods: ontological modelling design artifact DBpedia case study design principle
A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain
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2018 | Electronic Markets | Citations: 0
Authors: Stróżyna, Milena; Eiden, Gerd; Abramowicz, Witold; Filipiak, Dominik; Małyszko, Jacek; Węcel, Krzysztof

Abstract: The paper presents a proposal for a framework for the identification, assessment ... Expand

Abstract: The paper presents a proposal for a framework for the identification, assessment and selection of open data sources based on certain quality criteria, such as accessibility, relevance, accuracy & reliability, clarity, timeliness & punctuality, and coherence & comparability. The framework concerns mainly open data sources and focuses on their quality. The open data are used to enhance existing internal data and to fuse them with data from other sources. The framework consists of few steps starting from definition of quality criteria based on review of relevant literature and user requirements, then identification of potential sources, sources assessment and selection, and finally data retrieval process. For each step, a specific approach is described, how it may be conducted in practice. The proposed framework is evaluated using a real use case scenario from the maritime domain. The main approach utilized in this use-case is the Delphi method with some characteristics of Analytic Hierarchy Process. Collapse

Semantic filters: DBpedia

Topics: internet technology open data data quality user requirement decision making

Methods: survey delphi study literature study company material structured literature research
An Ontology-based Approach for Software Architecture Recommendations

2017 | Americas Conference on Information Systems | Citations: 0
Authors: Bhat, Manoj; Shumaiev, Klym; Biesdorf, Andreas; Hohenstein, Uwe; Hassel, Michael; Matthes, Florian

Abstract: The design and development of sustainable software systems require software arch ... Expand

Abstract: The design and development of sustainable software systems require software architects to consider a variety of architectural solutions and their trade-offs. With the frequent introduction of new architectural methods and software solutions, as well as, due to time-to-market constraints faced by software architects, considering even a subset of alternative architectural solutions during the decision-making process is a challenge. In this paper, we propose a recommendation system that automatically annotates architectural elements in software architecture documents and then proposes a) alternative architectural solutions for the annotated elements and b) concrete software solutions to realize an architectural design decision. These annotations and recommendations are derived from the knowledge captured in a publicly available cross-domain ontology. The evaluation of the recommendation system indicates that our approach can effectively support software architects to consider alternative architectural solutions while making architectural design decisions. Collapse

Semantic filters: DBpedia

Topics: knowledge representation recommender system enterprise architecture database system relational database

Methods: DBpedia ontological modelling machine learning design pattern existing ontologies
GAWA – Manager for accessibility Wayfinding apps
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2017 | International Journal of Information Management | Citations: 0
Authors: Rodriguez-Sanchez, M.C.; Martinez-Romo, Juan

Abstract: With this work, we propose and validate a new service system in the context of W ... Expand

Abstract: With this work, we propose and validate a new service system in the context of Wayﬁnding services to improve the SmartCities mechanism: smart mobility, smart people, smart governance and smart living services. Steering and navigation tasks through an environment constitute an essential activity in our daily lives. They have a high degree of practical value in a variety of domains, such as public area design, architectural Wayﬁnding, geopositioning and navigation, as well as urban planning and environmental design. At times, people with a visual impairment may also have problems in navigating autonomously and without personal assistance, especially in unknown environments (outdoor and indoor) using a smartphone. There could also be emergency situations in which the receiving of information in real time could be crucial. People with motor disabilities usually need information to avoid environments with obstacles, to arrive at a target or to manage touchscreens in daily activities and diﬀerent environments. The use of landmarks is therefore vitally important in human navigation. Wayﬁnding systems must change, given that according to the United Nations (UN) Development Program, people with a disability represent around 10% of the world’s population, which is approximately 650 million people. Additionally, according to the World Health Organization, the world’s population of people 60 years of age and older has doubled since 1980 and is predicted to reach 2 billion by 2050. Most Wayﬁnding applications in the Smartphone market suﬀer from at least one of the following problems: the information is not dynamic, the design is not universal or the interface is not adapted to diﬀerent users and preferences. Accordingly, apps do not currently have a universal design. The GAWA platform provides a universal and accessible solution to manage Wayﬁnding applications that focuses on people with a disability in outdoor and indoor environments in Smartcities. According to the results, the platform could be used for performing activities in their daily lives. Collapse

Semantic filters: DBpedia

Topics: smartphone mobile application global navigation satellite system Bluetooth Android

Methods: case study computational algorithm survey simulation DBpedia
Design Theory for Market Surveillance Systems
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2015 | Journal of Management Information Systems | Citations: 9
Authors: Li, Xin; Sun, Sherry X.; Chen, Kun; Fung, Terrance; Wang, Huaiqing

Abstract: Market surveillance systems (MSSs) are information systems that monitor financia ... Expand

Abstract: Market surveillance systems (MSSs) are information systems that monitor financial markets to combat market abuses. Existing MSSs focus mainly on analyzing trading activities and are often developed through a trial-and-error approach by screening data mining algorithms and features. The void of theoretical direction limits the effectiveness of MSSs and calls for the development of a design theory based on a thorough examination of the meta-requirements of MSSs. Based on the efficient market hypothesis and text understanding theory, this paper argues that market information analysis should be incorporated into MSSs and commonsense knowledge should be employed to connect related events to transactions and provide reference concepts for understanding market context and assessing transaction risk. We show the effectiveness of this proposed design theory through developing and evaluating a prototype system in the context of a real-world stock exchange market. By taking a theory-driven approach, this research shows the possibility and provides guidelines on the use of market information analysis to alleviate the market surveillance problem, which has significant implications for financial markets and the economy given the explosive growth of illegal trading activities worldwide. Collapse

Semantic filters: DBpedia

Topics: knowledge base knowledge representation usability search engine innovation management

Methods: design theory machine learning natural language processing design process design methodology

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Found 11 articles

Exploiting Linked Open Data for a Collaborative Filtering Recommendation System

An Approach to Extracting Topic-guided Views from the Sources of a Data Lake

Geo-semantic-parsing: AI-powered geoparsing by traversing semantic knowledge graphs

CrisMap: a Big Data Crisis Mapping System Based on Damage Detection and Geoparsing

Practical parallel string matching framework for RDF entailments with GPUs

Dependency modelling for inconsistency management in Digital Preservation – The PERICLES approach

A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain

An Ontology-based Approach for Software Architecture Recommendations

GAWA – Manager for accessibility Wayfinding apps

Design Theory for Market Surveillance Systems