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Planning a visit to Expo Milano 2015 or simply touring in Milan are activities that require a certain amount of a priori knowledge of the city. In this paper, we present the process of building such comprehensive knowledge bases that contain descriptions of events and activities, places and sights, transportation facilities as well as social activities, collected from numerous static, near- and real-time local and global data providers, including hyper local sources such as the Expo Milano 2015 official services and several social media platforms. Entities in the 3cixty KB are deduplicated, interlinked and enriched using semantic technologies. The 3cixty KB is empowering the ExplorMI 360 multi-device application, which has been officially endorsed by the E015 Technical Management Board and has gained the patronage of Expo Milano in 2015, thus has offered a unique testing scenario for the 20 million visitors along the 6 months of the exhibit. In 2016-2017, new knowledge bases have been created for the cities of London, Madeira and Singapore, as well as for the entire French Cote d'Azur area. The 3cixty KB is accessible at https://kb.3cixty.com/sparql while ExplorMI 360 at https://www.3cixty.com and in the Google Play Store and Apple App Store.
The large number of tweets generated daily is providing decision makers with means to obtain insights into recent events around the globe in near real-time. The main barrier for extracting such insights is the impossibility of manual inspection of a diverse and dynamic amount of information. This problem has attracted the attention of industry and research communities,resulting in algorithms for the automatic extraction of semantics in tweets and linking them to machine readable resources. While a tweet is shallowly comparable to any other textual content, it hides a complex and challenging structure that requires domain-specific computational approaches for mining semantics from it. The NEEL challenge series, established in 2013, has contributed to the collection of emerging trends in the field and definition of standardised benchmark corpora for entity recognition and linking in tweets, ensuring high quality labelled data that facilitates comparisons between different approaches. This article reports the findings and lessons learnt through an analysis of specific characteristics of the created corpora, limitations, lessons learnt from the different participants and pointers for furthering the field of entity recognition and linking in tweets.
Planning a visit to Expo Milano 2015 or simply touring in Milan are activities that require a certain amount of a priori knowledge of the city. In this paper, we present the process of building such a comprehensive knowledge base, the 3cixty KB, that contains descriptions of events, places, transportation facilities and social activities, collected from numerous static, near-and real-time local and global data providers, including Expo Milano 2015 official services and several social media platforms. Entities in the 3cixty KB are deduplicated, interlinked and enriched using semantic technologies. The 3cixty KB is empowering the Ex-plorMI 360 multi-device application, which has been officially endorsed by the E015 Technical Management Board and has gained the patronage of Expo Milano 2015, thus offering a unique testing scenario for the 20 million expected visitors along the 6 months of the exhibit. As of Septem-ber 7th, 2015 the 3cixty KB contains unique descriptions of 18, 665 events, 758 artists, 225, 552 places, 9, 342 transportation facilities, 95, 570 illustrating photos and 94, 789 reviews contributed by 81, 944 users. The 3cixty KB is accessible at http://3cixty.eurecom.fr/sparql while ExplorMI 360 at https://www.3cixty.com.
Location-based social networks (LBSN) are capturing large amount of data related to whereabouts of their users. This has become a social phenomenon, that is changing the normal communication means and it opens new research perspectives on how to compute descriptive models out of this collection of geo-spatial data. In this paper, we propose a methodology for clustering location-based information in order to provide first glance summaries of geographic areas. The summaries are a composition of fingerprints, each being a cluster, generated by a new subspace clustering algorithm, named GeoSubClu, that is proposed in this paper. The algorithm is parameter-less: it automatically recognizes areas with homogeneous density of similar points of interest and provides clusters with a rich characterization in terms of the representative categories. We measure the validity of the generated clusters using both a qualitative and a quantitative evaluation. In the former, we benchmark the results of our methodology over an existing gold standard, and we compare the achieved results against two baselines. We then further validate the generated clusters using a quantitative analysis, over the same gold standard and a new geographic extent, using statistical validation measures. Results of the qualitative and quantitative experiments show the robustness of our approach in creating geographic clusters which are significant both for humans (holding a F-measure of 88.98% over the gold standard) and from a statistical point of view.