Structuring free-form tagging in online news

Tagging has become one of the key activities in next generation websites which allow users selecting short labels to annotate, manage, and share multimedia information such as photos, videos and bookmarks. Tagging does not require users any prior training before participating in the annotation activities as they can freely choose any terms which best represent the semantic of contents without worrying about any formal structure or ontology. However, the practice of free-form tagging can lead to several problems, such as synonymy, polysemy and ambiguity, which potentially increase the complexity of managing the tags and retrieving information. To solve these problems, this research aims to construct a lightweight indexing scheme to structure tags by identifying and disambiguating the meaning of terms and construct a knowledge base or dictionary. News has been chosen as the primary domain of application to demonstrate the benefits of using structured tags for managing the rapidly changing and dynamic nature of news information. One of the main outcomes of this work is an automatically constructed vocabulary that defines the meaning of each named entity tag, which can be extracted from a news article (including person, location and organisation), based on experts suggestions from major search engines and the knowledge from public database such as Wikipedia. To demonstrate the potential applications of the vocabulary, we have used it to provide more functionalities in an online news website, including topic-based news reading, intuitive tagging, clipping and sharing of interesting news, as well as news filtering or searching based on named entity tags. The evaluation results on the impact of disambiguating tags have shown that the vocabulary can help to significantly improve news searching performance. The preliminary results from our user study have demonstrated that users can benefit from the additional functionalities on the news websites as they are able to retrieve more relevant news, clip and share news with friends and families effectively.

Randomized controlled trial of cognitive-behavioural therapy for coexisting depression and alcohol problems : short-term outcome

AIMS: Alcohol use disorders and depression co-occur frequently and are associated with poorer outcomes than when either condition occurs alone. The present study (Depression and Alcohol Integrated and Single-focused Interventions; DAISI) aimed to compare the effectiveness of brief intervention, single-focused and integrated psychological interventions for treatment of coexisting depression and alcohol use problems. METHODS: Participants (n = 284) with current depressive symptoms and hazardous alcohol use were assessed and randomly allocated to one of four individually delivered interventions: (i) a brief intervention only (single 90-minute session) with an integrated focus on depression and alcohol, or followed by a further nine 1-hour sessions with (ii) an alcohol focus; (iii) a depression focus; or (iv) an integrated focus. Follow-up assessments occurred 18 weeks after baseline. RESULTS: Compared with the brief intervention, 10 sessions were associated with greater reductions in average drinks per week, average drinking days per week and maximum consumption on 1 day. No difference in duration of treatment was found for depression outcomes. Compared with single-focused interventions, integrated treatment was associated with a greater reduction in drinking days and level of depression. For men, the alcohol-focused rather than depression-focused intervention was associated with a greater reduction in average drinks per day and drinks per week and an increased level of general functioning. Women showed greater improvements on each of these variables when they received depression-focused rather than alcohol-focused treatment. CONCLUSIONS: Integrated treatment may be superior to single-focused treatment for coexisting depression and alcohol problems, at least in the short term. Gender differences between single-focused depression and alcohol treatments warrant further study.

Improvement to Chinese information retrieval by incorporating word segmentation and query expansion

The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.

Building resilience to prevent mental health problems in young people : The resourceful adolescent programme (RAP)

This chapter describes an evidence-based programme called the Resourceful Adolescent Program (RAP), which has been successful in building resilience in young people to prevent depressive symptoms developing.The programme adopts a strengths-focused approach. It aims to build a range of coping resources that foster teenagers’ abilities to maintain a positive sense of self and regulate emotions in the face of the vicissitudes of everyday struggles and difficult life events.This groupbased programme can be implemented routinely in schools or by counselling professionals as an early intervention or prevention programme. While there is no universal definition, ‘resilience’ generally means the process of avoiding the negative trajectories associated with exposure to risk factors (Fergus and Zimmerman, 2005). Current models of resilience are also very clear that there ‘are many pathways to resilience’ (Bonanno, 2004) and there is no

Google book search settlement : implications for Australia

In 2005, the Association of American Publishers (AAP) and the Authors Guild (AG) sued Google for ‘massive copyright infringement’ for the mass digitization of books for the Google Book Search Project. In 2008, the parties reached a settlement, pending court approval. If approved, the settlement could have far-reaching consequences for authors, libraries, educational institutions and the reading public. In this article, I provide an overview of the Google Book Search Settlement. Firstly, I explain the Google Book Search Project, the legal questions raised by the Project and the lawsuit brought against Google. Secondly, I examine the terms of the Settlement Agreement, including what rights were granted between the parties and what rights were granted to the general public. Finally, I consider the implications of the settlement for Australia. The Settlement Agreement, and consequently the broader scope of the Google Book Search Project, is currently limited to the United States. In this article I consider whether the Project could be extended to Australia at a later date, how Google might go about doing this, and the implications of such an extension under the Copyright Act 1968 (Cth). I argue that without prior agreements with rightholders, our limited exceptions to copyright infringement mean that Google is unlikely to be able to extend the full scope of the Project to Australia without infringing copyright.