187,061 research outputs found
Trolls Identification within an Uncertain Framework
The web plays an important role in people's social lives since the emergence
of Web 2.0. It facilitates the interaction between users, gives them the
possibility to freely interact, share and collaborate through social networks,
online communities forums, blogs, wikis and other online collaborative media.
However, an other side of the web is negatively taken such as posting
inflammatory messages. Thus, when dealing with the online communities forums,
the managers seek to always enhance the performance of such platforms. In fact,
to keep the serenity and prohibit the disturbance of the normal atmosphere,
managers always try to novice users against these malicious persons by posting
such message (DO NOT FEED TROLLS). But, this kind of warning is not enough to
reduce this phenomenon. In this context we propose a new approach for detecting
malicious people also called 'Trolls' in order to allow community managers to
take their ability to post online. To be more realistic, our proposal is
defined within an uncertain framework. Based on the assumption consisting on
the trolls' integration in the successful discussion threads, we try to detect
the presence of such malicious users. Indeed, this method is based on a
conflict measure of the belief function theory applied between the different
messages of the thread. In order to show the feasibility and the result of our
approach, we test it in different simulated data.Comment: International Conference on Tools with Artificial Intelligence -
ICTAI , Nov 2014, Limassol, Cypru
Grounding semantics in robots for Visual Question Answering
In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning
Hi, how can I help you?: Automating enterprise IT support help desks
Question answering is one of the primary challenges of natural language
understanding. In realizing such a system, providing complex long answers to
questions is a challenging task as opposed to factoid answering as the former
needs context disambiguation. The different methods explored in the literature
can be broadly classified into three categories namely: 1) classification
based, 2) knowledge graph based and 3) retrieval based. Individually, none of
them address the need of an enterprise wide assistance system for an IT support
and maintenance domain. In this domain the variance of answers is large ranging
from factoid to structured operating procedures; the knowledge is present
across heterogeneous data sources like application specific documentation,
ticket management systems and any single technique for a general purpose
assistance is unable to scale for such a landscape. To address this, we have
built a cognitive platform with capabilities adopted for this domain. Further,
we have built a general purpose question answering system leveraging the
platform that can be instantiated for multiple products, technologies in the
support domain. The system uses a novel hybrid answering model that
orchestrates across a deep learning classifier, a knowledge graph based context
disambiguation module and a sophisticated bag-of-words search system. This
orchestration performs context switching for a provided question and also does
a smooth hand-off of the question to a human expert if none of the automated
techniques can provide a confident answer. This system has been deployed across
675 internal enterprise IT support and maintenance projects.Comment: To appear in IAAI 201
Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams
Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology
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