Roberto Yus

SHERLOCK: Semantic management of Location-Based Services in wireless environments

Abstract Location-Based Services (LBSs) are attracting great interest nowadays, mainly due to the economic value they can provide. So, different applications are being developed for tracking, navigation, advertising, etc., but most of those applications are designed for specific scenarios and goals with implicit knowledge about the application context. However, currently it is a challenge to provide a common framework that allows us to manage knowledge obtained from data sent by heterogeneous moving objects (textual data, multimedia data, sensor data, etc.). Moreover, the challenge is even greater considering situations where the system must adapt itself to contexts where the knowledge changes dynamically and in which moving objects can use different underlying wireless technologies and positioning systems. In this paper we present the system SHERLOCK, that offers a common framework with new functionalities for LBSs. Our system processes user requests continuously to provide up-to-date answers in heterogeneous and dynamic contexts. Ontologies and semantic techniques are used to share knowledge among devices, which enables the system to guide the user selecting the service that best fits his/her needs in the given context. Moreover, the system uses mobile agent technology to carry out the processing tasks wherever necessary in the dynamic underlying networks at any time.

Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity Systems

We describe UMBC’s systems developed for the SemEval 2014 tasks on Multilingual Semantic Textual Similarity (Task 10) and Cross-Level Semantic Similarity (Task 3). Our best submission in the Multilingual task ranked second in both English and Spanish subtasks using an unsupervised approach. Our best systems for Cross-Level task ranked second in Paragraph-Sentence and first in both Sentence-Phrase and Word-Sense subtask. The system ranked first for the PhraseWord subtask but was not included in the official results due to a late submission.

A friendly location-aware system to facilitate the work of technical directors when broadcasting sport events

The production costs of broadcasting sport events that require tracking moving objects are continuously increasing. Although those events are very demanded by the audience, broadcasting organizations have economical difficulties to afford them. For that reason, they are demanding the development of new professional software and hardware equipments that lead to a considerable reduction of the production costs. In this paper, we present a software system that takes into account these needs. This system allows a technical director to indicate his/her interest about certain moving objects or geographic areas in run-time. The system is in charge of selecting the cameras that can provide the types of views requested on those interesting objects and areas. So, it decreases the human effort needed to produce create, edit and distribute audiovisual contents, giving at the same time the opportunity to increase their quality. For this, the system provides a friendly interface to specify requirements and obtain which monitoring video cameras attached to moving or static objects fulfill them, along with a query processor to handle those requests in a continuous and efficient way. We illustrate the feasibility of our system in a specific scenario using real data of a traditional rowing race in the Basque Country.

Semantic reasoning on mobile devices

The massive spread of mobile computing in our daily lives has attracted a huge community of mobile application (apps) developers. These developers can take advantage of the benefits of semantic technologies (such as knowledge sharing and reusing, and knowledge decoupling) to enhance their applications. Moreover, the use of semantic reasoners would enable them to create more intelligent applications capable of discovering new knowledge, inferred from the available information.However, using semantic APIs and reasoners on current mobile devices is not a trivial task. In this paper, we show that the most popular current available Description Logics (DL) reasoners can be used on Android-based devices, and detail the efforts needed to port them to the Android platform. We also analyze the performance of these reasoners on current smartphones/tablets against more than 300 ontologies from the ORE?2013 ontology set, showing that, despite a notable difference with respect to desktop computers, their use is feasible.

Demo: FaceBlock: privacy-aware pictures for google glass

Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services

Robust semantic text similarity using LSA, machine learning, and linguistic resources

Semantic textual similarity is a measure of the degree of semantic equivalence between two pieces of text. We describe the SemSim system and its performance in the *SEM 2013 and SemEval-2014 tasks on semantic textual similarity. At the core of our system lies a robust distributional word similarity component that combines latent semantic analysis and machine learning augmented with data from several linguistic resources. We used a simple term alignment algorithm to handle longer pieces of text. Additional wrappers and resources were used to handle task specific challenges that include processing Spanish text, comparing text sequences of different lengths, handling informal words and phrases, and matching words with sense definitions. In the *SEM 2013 task on Semantic Textual Similarity, our best performing system ranked first among the 89 submitted runs. In the SemEval-2014 task on Multilingual Semantic Textual Similarity, we ranked a close second in both the English and Spanish subtasks. In the SemEval-2014 task on Cross-Level Semantic Similarity, we ranked first in Sentence–Phrase, Phrase–Word, and Word–Sense subtasks and second in the Paragraph–Sentence subtask.

SHERLOCK: a system for location-based services in wireless environments using semantics

Nowadays people are exposed to huge amounts of information that are generated continuously. However, current mobile applications, Web pages, and Location-Based Services (LBSs) are designed for specific scenarios and goals. In this demo we show the system SHERLOCK, which searches and shares up-to-date knowledge from nearby devices to relieve the user from knowing and managing such knowledge directly. Besides, the system guides the user in the process of selecting the service that best fits his/her needs in the given context.

Location-aware system based on a dynamic 3D model to help in live broadcasting of sport events

Broadcasting sport events in live is a challenging task because obtaining the best views requires taking into account many dynamic factors, such as: the location and movement of interesting objects, all the views provided by cameras in the scenario (some of them wireless, mobile, or attached to moving objects), possible occlusions, etc. Therefore, a technical director needs to manage a great amount of continuously changing information to quickly select the camera whose view should be broadcasted. In this paper, we present a location-aware system that helps technical directors in the broadcasting task, using a 3D model updated continuously with real-time location data retrieved from the scenario. They can indicate in run-time their interest in certain moving objects and the system is in charge of selecting the cameras that provide the kind of views required.

Real-time selection of video streams for live TV broadcasting based on Query-by-Example using a 3D model

The emergence of low-cost cameras with nearly professional features in the consumer market represents a new important source of video information. For example, using an increasing number of these cameras in live TV broadcastings enables obtaining varied contents without affecting the production costs. However, searching for interesting shots (e.g., a certain view of a specific car in a race) among many video sources in real-time can be difficult for a Technical Director (TD). So, TDs require a mechanism to easily and precisely represent the kind of shot they want to obtain abstracting them from the need to be aware of all the views provided by the cameras. In this paper we present our proposal to help a TD to visually define, using an interface for the definition of 3D scenes, an interesting sample view of one or more objects in the scenario. We recreate the views of the cameras in a 3D engine and apply 3D geometric computations on their virtual view, instead of analyzing the real images they provide, to enable an efficient and precise real-time selection. Specifically, our system computes a similarity measure to rank the candidate cameras. Moreover, we present a prototype of the system and an experimental evaluation that shows the interest of our proposal.

Emerging Semantic-Based Applications

In the last decade, we have witnessed the birth and spread of the Semantic Web and its associated semantic technologies. In this successful scenario, ontologies have played a crucial role. However, being knowledge representation frameworks as they are, the benefits of their use are beyond the WWW, but to many other different kind of systems, making it possible to design and develop smarter information systems which exploit the semantics of data.In this chapter, we present different semantic-based applications and projects that we have developed in the Distributed Information Systems (SID, in Spanish) research group of the University of Zaragoza. They address different application fields benefiting from semantic technologies to broaden their capabilities. In particular, we present our semantic systems for keyword-based search (QueryGen, Doctopush), information extraction (GENIE), fuzzy logic editing (Fuzzy OWL 2) and reasoning (fuzzy DL, DeLorean), and Location-Based Services managing (SHERLOCK).