Harnessing human computation for solving complex problems call spawns the issue of finding the unknown competitive group of solvers. In this paper, we propose an approach called Friendlysourcing to build up teams from social network answering a business call, all the while avoiding partial solution disclosure to competitive groups. The contributions of this paper include (i) a clustering based ...

This paper describes a new algorithm for discovering automatically possible meanings of unknown words from their phonetic features. It has been tested to obtain the semantics of a few invented verbs, using Levin’s verb classes.

This paper describes the participation of CERTH in the“Social Event Detection Task @ MediaEval 2011”, which aims at discovering social events in a large photo collection. The task comprises two challenges: (i) identification of soccer events in the cities of Barcelona and Rome, and (ii) identification of events taking place in two specific venues. We adopt an approach that combines spatial and ...

We present AI Poincar\'e, a machine learning algorithm for auto-discovering conserved quantities using trajectory data from unknown dynamical systems. test it on five Hamiltonian systems, including the gravitational 3-body problem, and find that discovers not only all exactly quantities, but also periodic orbits, phase transitions breakdown timescales approximate conservation laws.

Predictive models deployed in the world may assign incorrect labels to instances with high confidence. Such errors or unknown unknowns are rooted in model incompleteness, and typically arise because of the mismatch between training data and the cases seen in the open world. As the models are blind to such errors, input from an oracle is needed to identify these failures. In this paper, we formu...

We propose Discovering Novel Anomalous Patterns (DAP), a new method for continual and automated discovery of anomalous patterns in general datasets. Currently, general methods for anomalous pattern detection attempt to identify data patterns that are unexpected as compared to “normal” system behavior. We propose a novel approach for discovering data patterns that are unexpected given a profile ...

This paper concerns the handling of out-of-vocabulary (OOV) words in the JUPITER weather information system. Specifically our objective is to deal with weather queries regarding unknown cities. We have implemented a system which can detect the presence of an unknown city name, and immediately propose a plausible spelling for that city. Potentially, the city can be dynamically incorporated into ...

This paper concerns the handling of out-of-vocabulary (OOV) words in the JUPITER weather information system. Specifically our objective is to deal with weather queries regarding unknown cities. We have implemented a system which can detect the presence of an unknown city name, and immediately propose a plausible spelling for that city. Potentially, the city can be dynamically incorporated into ...

Recently, the detection of previously unknown, frequently occurring pattern is regarded as a difficult problem. We call this pattern as “motif”. Many researchers have proposed algorithms for discovering the motif. However, if the optimal period length of the motif is not known in advance, we can not use their algorithms for discovering the motif. In this paper, we attempt to determine the optim...

Mucoepidermoid carcinoma (MEC) is one of the most common histological malignant salivary gland tumors, it frequently diagnosed in parotid gland. MEC also intra oral minor glands. Only a few cases tonsillar have been reported. We present rare case mucoepidermoid arising from left pharyngeal tonsil. This report shows that important to perform tonsillectomy when discovering neck metastasis tumors ...