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Tag Recommendation for Large-Scale Ontology-Based Information Systems

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Linked Books: un indice citazionale per la storia di Venezia

Matteo Romanello, Giovanni Colavizza

We present the outcomes of the Linked Books project, resulting in a prototype citation index interlinking the Italian national library catalog (Opac SBN) with the information system of the State Archive of Venice and international authority records or “met ...

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to ...

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Unleashing the power of semantic text analysis: a complex systems approach

Andrea Martini

In the present information era, a huge amount of machine-readable data is available regarding scientific publications. Such unprecedented wealth of data offers the opportunity to investigate science itself as a complex interacting system by means of quanti ...

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Using Networks to Visualize Publications

Dario Rodighiero

Retrieval systems are often shaped as lists organized in pages. However, the majority of users look at the first page ignoring the other ones. This presentation concerns an alterna- tive way to present the results of a query using network visualizations.  ...

2018

Detecting Trends in Job Advertisements

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We present an automatic method for trend detection in job ads. From a job-posting website, we collect job ads from 16 countries and in 8 languages and 6 job domains. We pre-process them by removing stop words, lemmatising and performing cross-domain filter ...

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Applications of Approximate Learning and Inference for Probabilistic Models

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We develop approximate inference and learning methods for facilitating the use of probabilistic modeling techniques motivated by applications in two different areas. First, we consider the ill-posed inverse problem of recovering an image from an underdeter ...

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Data Summarization with Social Contexts

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While social data is being widely used in various applications such as sentiment analysis and trend prediction, its sheer size also presents great challenges for storing, sharing and processing such data. These challenges can be addressed by data summariza ...

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Learning Explainable User Sentiment and Preferences for Information Filtering

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In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...

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Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

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This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messagi ...

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Word Embeddings for Natural Language Processing

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Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled text, such continuous space representations can be computed for c ...

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