Sleeping Beauty : global advertising self regulation awakens

The system of self regulation of advertising in mass-media was a dream scenario. If stakeholders complained and the advertisement was deemed offensive by an expert panel, it was an easy matter to withdraw the advertisement from mass media and from public attention. This was done locally, according to the cultural values and aesthetics of the population and the mandate of the self regulation board. To advertising regulators, the internet became their worst nightmare. The system of self regulation was no longer closed, and could be circumvented by placing the offending advertisements online. The system of self regulation was also no longer local, but global. All internet users had access to the same advertisements, regardless of cultural considerations. The awakening of global advertising self regulation is something that demands discussion. It is of value to all conference goers of AAA 2010 Europe, as it affects all advertising academics and all stakeholders in the advertising process. As the leading advertising body seeking to bring global advertising issues to a new venue in Europe, the AAA 2010 European Conference seems ripe for a special session on advertising self regulation. This is especially true as the panel contributes a European, US and Asia-Pacific viewpoint.

Like? Advertising practitioners views of social media as an advertising research tool

Given that both academics and marketers are dissatisfied with the current state of advertising research (Kerr and Schultz, 2010; Neff, 2011), the objective of this exploratory paper is to determine the position of world-leading advertising professionals on the use of social media to test, track and evaluate campaigns. Using Delphi methodology, an international panel of Cannes Gold Lion winners acknowledged that social media research has both strengths and weaknesses, the same as any research. Its strengths are its intimacy and spontaneity, bringing the brand and consumer closer. The real risk is the loss of control in this research environment.

Advertising and promotion : an integrated marketing communications perspective

This text explores the area of advertising and promotion practice. It shows how real organisations coordinate the various elements of the promotional mix with other marketing activities."--Provided by publisher

A two-stage approach for generating topic models

Topic modeling has been widely utilized in the fields of information retrieval, text mining, text classification etc. Most existing statistical topic modeling methods such as LDA and pLSA generate a term based representation to represent a topic by selecting single words from multinomial word distribution over this topic. There are two main shortcomings: firstly, popular or common words occur very often across different topics that bring ambiguity to understand topics; secondly, single words lack coherent semantic meaning to accurately represent topics. In order to overcome these problems, in this paper, we propose a two-stage model that combines text mining and pattern mining with statistical modeling to generate more discriminative and semantic rich topic representations. Experiments show that the optimized topic representations generated by the proposed methods outperform the typical statistical topic modeling method LDA in terms of accuracy and certainty.

How much is that data in the window? Advertising your research data with QUT Library

Queensland University of Technology (QUT) Library offers a range of resources and services to researchers as part of their research support portfolio. This poster will present key features of two of the data management services offered by research support staff at QUT Library. The first service is QUT Research Data Finder (RDF), a product of the Australian National Data Service (ANDS) funded Metadata Stores project. RDF is a data registry (metadata repository) that aims to publicise datasets that are research outputs arising from completed QUT research projects. The second is a software and code registry, which is currently under development with the sole purpose of improving discovery of source code and software as QUT research outputs. RESEARCH DATA FINDER As an integrated metadata repository, Research Data Finder aligns with institutional sources of truth, such as QUT’s research administration system, ResearchMaster, as well as QUT’s Academic Profiles system to provide high quality data descriptions that increase awareness of, and access to, shareable research data. The repository and its workflows are designed to foster better data management practices, enhance opportunities for collaboration and research, promote cross-disciplinary research and maximise the impact of existing research data sets. SOFTWARE AND CODE REGISTRY The QUT Library software and code registry project stems from concerns amongst researchers with regards to development activities, storage, accessibility, discoverability and impact, sharing, copyright and IP ownership of software and code. As a result, the Library is developing a registry for code and software research outputs, which will use existing Research Data Finder architecture. The underpinning software for both registries is VIVO, open source software developed by Cornell University. The registry will use the Research Data Finder service instance of VIVO and will include a searchable interface, links to code/software locations and metadata feeds to Research Data Australia. Key benefits of the project include:improving the discoverability and reuse of QUT researchers’ code and software amongst QUT and the QUT research community; increasing the profile of QUT research outputs on a national level by providing a metadata feed to Research Data Australia, and; improving the metrics for access and reuse of code and software in the repository.

Inward internationalization of consumer services : lessons from Australian firms

Purpose - The aim of this paper is to explore the inward internationalization process of consumer services. A review of the service internationalization literature is conducted and the resource-based view of the firm is used as a theoretical approach. Design/methodology - Case study methodology is used to explore the internationalization process of five different consumer service sectors: tourism, education, accommodation, transport and entertainment. The main data collection method was interviews conducted with top managers of 12 Australian consumer service firms from these sectors. Findings - Findings of this study show that inward internationalizing services confront most of their barriers, such as immigration policies, exchange rate fluctuations, and cultural differences, in the domestic market where the service is provided. The findings also suggest that superior intentional performance for consumer service firms combines firm-specific resources and capabilities, such as market orientation, service quality, cultural sensitivity, international communicational activities, partnerships and networks, with country-specific resources and capabilities, such as country-of-origin image and government support. Research limitations/implications - This is one of the few studies in the academic literature that directly addresses the issue of inward internationalization of consumer services. Limitations derive from the qualitative nature of this study. Practical implications - The process of inward internationalization applies to a broad range of service industries and can assist firms to develop more effective international marketing strategies. Originality/value - This study contributes to the international services literature by identifying the main barriers and drivers of international performance for inward internationalizing consumer service firms, which is a topic that has been neglected in the literature.

Pattern-based topic models for information filtering

Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering is rarely known. Patterns are always thought to be more representative than single terms for representing documents. In this paper, a novel information filtering model, Pattern-based Topic Model(PBTM) , is proposed to represent the text documents not only using the topic distributions at general level but also using semantic pattern representations at detailed specific level, both of which contribute to the accurate document representation and document relevance ranking. Extensive experiments are conducted to evaluate the effectiveness of PBTM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model achieves outstanding performance.

Regulating integrated advertising

This chapter approaches integrated advertising as a practice that is continuous with advertising history, rather than a phenomenon associated with new technologies. Competition for technology-enabled audiences in expanding media and entertainment markets is nonetheless an important factor in the turn to integrated advertising and marketing strategies in recent years. While integrated advertising provides solutions for advertisers, it is problematic for media consumers because it is not always distinguishable from surrounding program content and clearly identifiable as advertising. It creates opportunities for advertisers to fly below the radar of citizen and consumer awareness of commercial and political influences in media content, and for this reason has been constrained by regulation. Media regulators have come to play an important role in striking a balance between public and private interests in commercial media by setting and adjudicating the limits of integrated advertising practices. This chapter looks at how broadcasting regulators have responded to the challenges of regulating integrated advertising in commercial radio in three different territories (United States, United Kingdom and Australia). It draws attention to the ways in which integrated advertising simultaneously drives innovation in media genres and forms, as well as de-regulation of the influence exercised by advertisers in commercial media content.

Academic legal research and academic research capacity enhancement working topic : "purposes and objectives of law schools beyond educating students (research, capacity building,community service and outreach)"

One of the main objectives of law schools beyond educating students is to produce viable legal research. The comments in this paper are basically confined to the Australian context, and to examine this topic effectively, it is necessary to briefly review the current tertiary research agenda in Australia. This paper argues that there is a need for recognition and support for an expanded legal research framework along with additional research training for legal academics. There also needs to be more effective methods of measuring and recognising quality in legal research. This method needs to be one that can engender respect in an interdisciplinary context.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

A topic based document relevance ranking model

Topic modelling has been widely used in the fields of information retrieval, text mining, machine learning, etc. In this paper, we propose a novel model, Pattern Enhanced Topic Model (PETM), which makes improvements to topic modelling by semantically representing topics with discriminative patterns, and also makes innovative contributions to information filtering by utilising the proposed PETM to determine document relevance based on topics distribution and maximum matched patterns proposed in this paper. Extensive experiments are conducted to evaluate the effectiveness of PETM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models.

Revisiting sub-topic retrieval in the ImageCLEF 2009 photo retrieval task

Ranking documents according to the Probability Ranking Principle has been theoretically shown to guarantee optimal retrieval effectiveness in tasks such as ad hoc document retrieval. This ranking strategy assumes independence among document relevance assessments. This assumption, however, often does not hold, for example in the scenarios where redundancy in retrieved documents is of major concern, as it is the case in the sub–topic retrieval task. In this chapter, we propose a new ranking strategy for sub–topic retrieval that builds upon the interdependent document relevance and topic–oriented models. With respect to the topic– oriented model, we investigate both static and dynamic clustering techniques, aiming to group topically similar documents. Evidence from clusters is then combined with information about document dependencies to form a new document ranking. We compare and contrast the proposed method against state–of–the–art approaches, such as Maximal Marginal Relevance, Portfolio Theory for Information Retrieval, and standard cluster–based diversification strategies. The empirical investigation is performed on the ImageCLEF 2009 Photo Retrieval collection, where images are assessed with respect to sub–topics of a more general query topic. The experimental results show that our approaches outperform the state–of–the–art strategies with respect to a number of diversity measures.

Towards a global framework for advertising self regulation

One of the forces which has indelibly shaped marketing is the internet. It has not only changed the way we communicate, but our marketing practices and our advertising self-regulation process (Kerr, Mortimer, Dickinson and Waller 2012). This special session seeks to build a new global framework to regulate advertising activity in this uncharted online environment. It looks back to how advertising has been traditionally self-regulated and looks forward to identify the key issues for marketers, consumers, regulators and the media. This special session explores and reinforces the fundamental purpose of the conference, as well as addressing the urgent needs of marketers, consumers and regulators.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.