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McCarthy, Kevin
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McCarthy, Kevin
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McCarthy, Kevin
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Now showing 1 - 10 of 22
- PublicationThe pursuit of happiness : searching for worthy followees on twitterWe are living in an age of information overload, where it can be difficult to define which information is relevant and important to the end user at a point in time. In this paper, we introduce a solution to apportioning this constant flow of information by going to the source of the content, namely the producers. This paper examines an application for searching for pertinent friends on the popular microblogging service, Twitter1 and our approach to curtail the cold start problem that new users of the service face. We introduce our search technology which is capable of finding the producers of wanted content and suggest connecting to them as followees on Twitter. We also prove the usefulness of this technology through the results of a live user experiment carried out on these cold start users.
1612 - PublicationUsing social ties in group recommendationThe social web is a mass of activity, petabytes of data are generated yearly. The social web has proven to be a great resource for new recommender system techniques and ideas. However it would appear that typically these techniques are not so social, as they only generate recommendations for a user acting alone. In this paper we take the social graph data and preference content (via Facebook) of 94 user study participants and generate social group recommendations for them and their friends. We evaluate how different aggregation policies perform in deciding the final group recommendation. Our findings show that in an offline evaluation an aggregation policy which takes into consideration social weighting outperforms other aggregation policies.
779 - PublicationMining Features and Sentiment from Review Experiences(Springer, 2013-07-11)
; ; ; ; Supplementing product information with user-generated content such as ratings and reviews can help to convert browsers into buyers. As a result this type of content is now front and centre for many major e-commerce sites such as Amazon. We believe that this type of content can provide a rich source of valuable information that is useful for a variety of purposes. In this work we are interested in harnessing past reviews to support the writing of new useful reviews, especially for novice contributors. We describe how automatic topic extraction and sentiment analysis can be used to mine valuable information from user-generated reviews, to make useful suggestions to users at review writing time about features that they may wish to cover in their own reviews. We describe the results of a live-user trial to show how the resulting system is capable of delivering high quality reviews that are comparable to the best that sites like Amazon have to offer in terms of information content and helpfulness.438Scopus© Citations 9 - PublicationCombining similarity and sentiment in opinion mining for product recommendation(Springer, 2016-04)
; ; ; ; In the world of recommender systems, so-called content-based methods are an important approach that rely on the availability of detailed product or item descriptions to drive the recommendation process. For example, recommendations can be generated for a target user by selecting unseen products that are similar to the products that the target user has liked or purchased in the past. To do this, content-based methods must be able to compute the similarity between pairs of products (unseen products and liked products, for example) and typically this is achieved by comparing product features or other descriptive elements. The approach works well when product descriptions are readily available and when they are detailed enough to afford an effective similarity comparison. But this is not always the case. Detailed product descriptions may not be available since they can be expensive to create and maintain. In this article we consider another source of product descriptions in the form of the user-generated reviews that frequently accompany products on the web. We ask whether it is possible to mine these reviews, unstructured and noisy as they are, to produce useful product descriptions that can be used in a recommendation system. In particular we describe a novel approach to product recommendation that harnesses not only the features that can be mined from user-generated reviews but also the expressions of sentiment that are associated with these features. We present a recommendation ranking strategy that combines similarity and sentiment to suggest products that are similar but superior to a query product according to the opinion of reviewers, and we demonstrate the practical benefits of this approach across a variety of Amazon product domains.2144Scopus© Citations 53 - PublicationPersonalized and automatic social summarization of events in videoSocial services like Twitter are increasingly used to provide a conversational backdrop to real-world events in real-time. Sporting events are a good example of this and this year, millions of users tweeted their comments as they watched the World Cup matches from around the world. In this paper, we look at using these time-stamped opinions as the basis for generating video highlights for these soccer matches. We introduce the PASSEV system and describe and evaluate two basic summarization approaches.
1546Scopus© Citations 34 - PublicationPower to the people : exploring neighbourhood formations in social recommender systemsThe explosive growth of online social networks in recent times has presented a powerful source of information to be utilised in personalised recommendations. Unsurprisingly there has already been a large body of work completed in the recommender system field to incorporate this social in- formation into the recommendation process. In this paper we examine the practice of leveraging a user’s social graph in order to generate recommendations. Using various neighbourhood selection strategies, we examine the user satisfaction and the level of perceived trust in the recommendations received.
1453Scopus© Citations 17 - PublicationThe social camera : a case-study in contextual image recommendationThe digital camera revolution has changed the world of photography and now most people have access to, and even regularly carry, a digital camera. Often these cameras have been designed with simplicity in mind: they harness a variety of sophisticated technologies in order to automatically take care of all manner of complex settings (aperture, shutter speed, flash etc.) for point-and-shoot ease, these assistive features are usually incorporated directly into the cameras interface. However, there is little or no support for the end-user when it comes to helping them to compose or frame a scene. To this end we describe a novel recommendation process which uses a variety of intelligent and assistive interfaces to guide the user in taking relevant compositions given their current location and scene context. This application has been implemented on the Android platform and we describe its core user interaction, recommendation technologies and demonstrate its effectiveness in a number of real-world scenarios. Specifically we report on the results of a live-user trial of the technology in a real-world tourist setting.
1465Scopus© Citations 20 - PublicationThe Demonstration of the Reviewer's Assistant(ACM, 2012-09)
; ; ; ; User generated reviews are now a familiar and valuable part of most e-commerce sites since high quality reviews are known to influence purchasing decisions. In this demonstration we describe work on the Reviewer's Assistant (RA), which is a recommendation system that is designed to help users to write better quality reviews. It does this by suggesting relevant topics that they may wish to discuss based on the product they are reviewing and the content of their review so far.552 - PublicationLiquid-phase 3D bioprinting of gelatin alginate hydrogels: influence of printing parameters on hydrogel line width and layer height(Springer Science and Business Media LLC, 2019-07-16)
; ; ; ; Extrusion-based 3D bioprinting is a direct deposition approach used to create three-dimensional (3D) tissue scaffolds typically comprising hydrogels. Hydrogels are hydrated polymer networks that are chemically or physically cross-linked. Often, 3D bioprinting is performed in air, despite the hydrated nature of hydrogels and the potential advantage of using a liquid phase to provide cross-linking and otherwise functionalize the hydrogel. In this work, we print gelatin alginate hydrogels directly into a cross-linking solution of calcium chloride and investigate the influence of nozzle diameter, distance between nozzle and surface, calcium chloride concentration, and extrusion rate on the dimensions of the printed hydrogel. The hydrogel layer height was generally found to increase with increasing extrusion rate and nozzle distance, according to the increased volume extruded and the available space, respectively. In addition, the hydrogel width was generally found to increase with decreasing nozzle distance and cross-linking concentration corresponding to confinement-induced spreading and low cross-linking regimes, respectively. Width/height ratios of ~ 1 were generally achieved when the nozzle diameter and distance were comparable above a certain cross-linking concentration. Using these relationships, biocompatible 3D multilayer structures were successfully printed directly into calcium chloride cross-linking solution.666Scopus© Citations 27 - PublicationUsing Twitter to recommend real-time topical newsRecommending news stories to users, based on their preferences,has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach to news recommendation that harnesses real-time micro-blogging activity, from a service such as Twitter, as the basis for promoting news stories from a user's favourite RSS feeds. A preliminary evaluation is carried out on an implementation of this technique that shows promising results.
21368Scopus© Citations 338