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Classifying sentiment in microblogs: Is brevity an advantage? 10

Classifying sentiment in microblogs: Is brevity an advantage...

引用

Proceedings of the 19th ACM international conference on Information and knowledge management

作者： Bermingham, Adam Smeaton, Alan CLARITY: Centre for Sensor Web Technologies School of Computing Dublin University Ireland

ISBN: (纸本)9781450300995

Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. However, this short length coupled with their noisy nature can pose difficulties for standard machine learning document representations. In this work we examine the hypothesis that it is easier to classify the sentiment in these short form documents than in longer form documents. Surprisingly, we find classifying sentiment in microblogs easier than in blogs and make a number of observations pertaining to the challenge of supervised learning for sentiment analysis in microblogs. © 2010 ACM.

关键词： Sentiment analysis

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Memorymesh - lifelogs as densely linked hypermedia 13

Memorymesh - lifelogs as densely linked hypermedia

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4th International SenseCam and Pervasive Imaging Conference, SenseCam 2013

作者： Zhou, Lijuan Marissa Gurrin, Cathal CLARITY Centre for Sensor Web Technologies School of Computing Dublin City University Ireland

ISBN: (纸本)9781450322478

Lifelogs are huge archives of multimedia data and consequently, they need to incorporate organization methodologies to fully exploit their potential. Early work in organizing lifelogs based on either video-style playback or event segmentation with browsing or basic search. In this work we propose that lifelogs can be represented as a densely linked hypermedia archive, called a MemoryMesh. We introduce how this can be constructed and the potential to improve retrieval performance. Copyright 2013 ACM.

关键词： Hypermedia systems

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Optimising the number of channels in EEG-augmented image search

Optimising the number of channels in EEG-augmented image sea...

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25th BCS onference on Human Computer Interaction, HCI 2011

作者： Healy, Graham Smeaton, Alan F. CLARITY: Centre for Sensor Web Technologies School of Computing Dublin City University Ireland

Recent proof-of-concept research has appeared showing the applicability of Brain Computer Interface (BCI) technology in combination with the human visual system, to classify images. The basic premise here is that images that arouse a participant's attention generate a detectable response in their brainwaves, measurable using an electroencephalograph (EEG). When a participant is given a target class of images to search for, each image belonging to that target class presented within a stream of images should elicit a distinctly detectable neural response. Previous work in this domain has primarily focused on validating the technique on proof of concept image sets that demonstrate desired properties and on examining the capabilities of the technique at various image presentation speeds. In this paper we expand on this by examining the capability of the technique when using a reduced number of channels in the EEG, and its impact on the detection accuracy.

关键词： Brain computer interface

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Mining user activity as a context source for search and retrieval

Mining user activity as a context source for search and retr...

引用

International Conference on Semantic Technology and Information Retrieval

作者： Qiu, Zhengwei Doherty, Aiden R. Gurrin, Cathal Smeaton, Alan F. CLARITY: Centre for Sensor Web Technologies School of Computing Dublin City University Ireland

ISBN: (纸本)9781612843537

Nowadays in information retrieval it is generally accepted that if we can better understand the context of searchers then this could help the search process, either at indexing time by including more metadata or at retrieval time by better modelling the user needs. In this work we explore how activity recognition from tri-axial accelerometers can be employed to model a user's activity as a means of enabling context-aware information retrieval. In this paper we discuss how we can gather user activity automatically as a context source from a wearable mobile device and we evaluate the accuracy of our proposed user activity recognition algorithm. Our technique can recognise four kinds of activities which can be used to model part of an individual's current context. We discuss promising experimental results, possible approaches to improve our algorithms, and the impact of this work in modelling user context toward enhanced search and retrieval. © 2011 IEEE.

关键词： Information retrieval

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Designing novel applications inspired by emerging media technologies

Designing novel applications inspired by emerging media tech...

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25th BCS onference on Human Computer Interaction, HCI 2011

作者： Lee, Hyowon Smeaton, Alan F. CLARITY: Centre for Sensor Web Technologies School of Computing Dublin City University Ireland

The field of Human-Computer Interaction provides a number of useful tools and methods for obtaining information on end-users and their usage context to inform the design of computer systems, yet relatively little is known on how to go about designing for a completely novel application where there is no user base, no existing practice of use available at the start. The success of the currently available HCI methodology that focuses on understanding users' needs and establishing requirements is well-deserved in making computing applications usable in terms of fitting them to end-users' usage contexts. However, too much emphasis on identifying user needs tends to stifle other more exploratory design activities where new types of applications are invented in order to discover or create new activities currently not practiced. In this paper, we argue that a great starting point of novel application design is not the problem space (trying to rigorously define the user requirements) but the solution space (trying to leverage emerging computational technologies and growing design knowledge for various interaction platforms), and we build a foundation for a pragmatic design methodology supported by the authors' extensive experience in designing novel applications inspired by emerging media technologies.

关键词： Human computer interaction

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Using Twitter to Detect and Tag Important Events in Live Sports 5

Using Twitter to Detect and Tag Important Events in Live Spo...

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5th International AAAI Conference on weblogs and Social Media, ICWSM 2011

作者： Lanagan, James Smeaton, Alan F. CLARITY: Centre For Sensor Web Technologies School of Computing Dublin City University Dublin Ireland

ISBN: (纸本)9781577355052

In this paper we examine the effectiveness of using a filtered stream of tweets from Twitter to automatically identify events of interest within the video of live sports transmissions. We show that using just the volume of tweets generated at any moment of a game actually provides a very accurate means of event detection, as well as an automatic method for tagging events with representative words from the tweet stream. We compare this method with an alternative approach that uses complex audio-visual content analysis of the video, showing that it provides near-equivalent accuracy for major event detection at a fraction of the computational cost. Using community tweets and discussion also provides a sense of what the audience themselves found to be the talking points of a video. Copyright © 2011, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Sports

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Context ontologies for recommending from the social web 13

Context ontologies for recommending from the social web

引用

3rd Workshop on Context-Awareness in Retrieval and Recommendation, CaRR 2013 - In Conjunction with the 6th ACM International Conference on web Search and Data Mining, WSDM 2013

作者： Hurrell, Eoin Smeaton, Alan F. CLARITY: Centre for Sensor Web Technologies School of Computing Dublin University Glasnevin Dublin 9 Ireland

ISBN: (纸本)9781450318471

Investigations into combining context and recommendation has resulted in much fruitful research which has improved recommender systems. Such contextual information has come in many forms and been used in different ways, successfully offering better in-situ suggestions. Factors such as location, time of recommendation, etc. have proven themselves as useful contributors to exploiting context. One issue, however, is the importance placed on each aspect of context, especially as new forms of recommendation are developed. Context is traditionally incorporated into recommenders at design-time, as a filter or as an integral part of how users are modelled, but the importance placed on each aspect is not often examined. Social recommenders and systems that draw on the wealth of data present in social networks frequently have access to far more contextual factors than traditional recommenders, making user relationships to these factors all the more important. The main contribution of this paper is to provide an examination of contextual priorities from the social web, which prove useful to recommender research in the area. This ontological examination of context shows that users have different priorities when it comes to context with a large variation in the suitability of each contextual factor in predicting good recommendations. In addition, this paper presents and discusses an approach to individually tailoring context ontologies (allowing for dynamically generated context sets), evaluating contextual factors in recommending from the social web. Copyright 2013 ACM.

关键词： Recommender systems

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Interactivity and multimedia in case-based recommendation

Interactivity and multimedia in case-based recommendation

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25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

作者： Hurrell, Eoin Smeaton, Alan F. Smyth, Barry CLARITY: Centre for Sensor Web Technologies School of Computing Dublin City University Glasnevin Dublin 9 Ireland

ISBN: (纸本)9781577355588

The increasingly prevalent view that recommendation is a conversation between user and system is driving a renewed interest in approaches to system design that involve the user in meaningful ways. In addition to this the proliferation of mobile devices and the near-ubiquity of sensing technologies means that there are now many opportunities to capture real-life experiences, in real-time, providing a new source of raw material for case-based reasoning. In this paper we consider the availability of real-world exercise information, in this cases corresponding to jogging routes, and methods by which we can involve a user in recommending such routes. Outlined here is a novel interaction methodology and compound recommendation system to recommend and adapt routes based on experience not distance/traffic avoidance or similar. We describe the Exercise Builder, a proof-of-concept application that attempts to help visitors to a new city to plan their jogging routes by combining case retrieval, interactive adaptation, and multimedia explanation in a single online service. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Case based reasoning

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The benefits of opening recommendation to human interaction

The benefits of opening recommendation to human interaction

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25th BCS onference on Human Computer Interaction, HCI 2011

作者： Hurrel, Eoin Smeaton, Alan F. CLARITY: Centre for Sensor Web Technologies School of Computing Dublin City University Glasnevin Dublin 9 Ireland

This paper describes work in progress that uses an interactive recommendation process to construct new objects which are tailored to user preferences. The novelty in our work is moving from the recommendation of static objects like consumer goods, movies or books, towards dynamically-constructed recommendations which are built as part of the recommendation process. As a proof-of-concept we build running or jogging routes for visitors to a city, recommending routes to users according to their preferences and we present details of this system.

关键词： Recommender systems

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Towards the profiling of twitter users for topic-based filtering

Towards the profiling of twitter users for topic-based filte...

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32nd SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2012

作者： Esparza, Sandra Garcia O'Mahony, Michael P. Smyth, Barry CLARITY: Centre for Sensor Web Technologies School of Computer Science and Informatics Dublin Ireland

ISBN: (纸本)9781447147381

There is no doubting the incredible impact of Twitter on how we communicate, access and share information online. Currently users can follow other users or hashtags in order to benefit from a stream of data from people they trust or on topics that matter to them. However at the moment the following granularity of Twitter means that users cannot limit their information streams to a set of topics by a given user. Thus, even the most carefully curated information streams can quickly become polluted with extraneous content. In this paper we describe our initial steps to improve this situation by proposing a profiling approach that can be used for information filtering purposes as well as recommendation purposes. First, we demonstrate that it is feasible to automatically profile the interests of users by using machine learning techniques to classify the pages that they share via their tweets. We then go on to describe how this profiling mechanism can be used to organise and filter Twitter information streams. In particular we present a system that provides for a more fine-grained way to follow users on specific topics and thereby refine the standard Twitter timeline based on a user's core topical interests. © Springer-Verlag London 2012.

关键词： Information filtering

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