Bahareh Rahmanzadeh Heravi

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Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each(More)
Increasingly, news breaks on social media, where ordinary citizens post images and videos and their own commentary in the form of text. This user generated content (UGC) is newsworthy information and invaluable for newsrooms. In order to incorporate this data into a news story, the journalist needs to process, compile and verify information on the social(More)
In this paper, we describe an approach to filter out noisy data generated by keywords-based tweet filtering methods by performing Word Sense Disambiguation on those keywords used to collect tweets. We present the noise filtering problem as a binary classification problem and discuss our evaluation strategy which is to be carried out in future. With growing(More)
Social media platforms have become an important source of information in course of a breaking news event, such as natural calamity, political uproar, etc. News organisations and journalists are increasingly realising the value of information being propagated via social media. However, the sheer volume of the data produced on social media is overwhelming and(More)
Automation of business transactions between trading partners is an important factor in today's global business. XML based E-Business standards are developed to provide a shared understanding on what information to share, when and how between trading partners. However these standards can only capture the syntax of the transactions and not the semantics. This(More)
Named Entity rEcognition and Linking (NEEL) from text is an essential task in many Natural Language Processing (NLP) applications because it enables a better understanding of the content. However in the context of Social Media , NEEL is challenging due to the higher level of writing mistakes, fast language dynamics and often lack of context. To this end, we(More)