Knowmore (House of Commons)

Knowmore (House of Commons) is a large scale generative interactive installation that incorporates embodied interaction, dynamic image creation, new furniture forms, touch sensitivity, innovative collaborative processes and multichannel generative sound creation. A large circular table spun by hand and a computer-controlled video projection falls on its top, creating an uncanny blend of physical object and virtual media. Participants’ presence around the table and how they touch it is registered, allowing up to five people to collaboratively ‘play’ this deeply immersive audiovisual work. Set within an ecological context, the work subtly asks what kind of resources and knowledges might be necessary to move us past simply knowing what needs to be changed to instead actually embodying that change, whilst hinting at other deeply relational ways of understanding and knowing the world. The work has successfully operated in two high traffic public environments, generating a subtle form of interactivity that allows different people to interact at different paces and speeds and with differing intentions, each contributing towards dramatic public outcomes. The research field involved developing new interaction and engagement strategies for eco-political media arts practice. The context was the creation of improved embodied, performative and improvisational experiences for participants; further informed by ‘Sustainment’ theory. The central question was, what ontological shifts may be necessary to better envision and align our everyday life choices in ways that respect that which is shared by all - 'The Commons'. The methodology was primarily practice-led and in concert with underlying theories. The work’s knowledge contribution was to question how new media interactive experience and embodied interaction might prompt participants to reflect upon the kind of resources and knowledges required to move past simply knowing what needs to be changed to instead actually embodying that change. This was achieved through focusing on the power of embodied learning implied by the works' strongly physical interface (i.e. the spinning of a full size table) in concert with the complex field of layered imagery and sound. The work was commissioned by the State Library of Queensland and Queensland Artworkers Alliance and significantly funded by The Australia Council for the Arts, Arts Queensland, QUT, RMIT Centre for Animation and Interactive Media and industry partners E2E Visuals. After premiering for 3 months at the State Library of Queensland it was curated into the significant ‘Mediations Biennial of Modern Art’ in Poznan, Poland. The work formed the basis of two papers, was reviewed in Realtime (90), was overviewed at Subtle Technologies (2010) in Toronto and shortlisted for ISEA 2011 Istanbul and included in the edited book/catalogue ‘Art in Spite of Economics’, a collaboration between Leonardo/ISAST (MIT Press); Goldsmiths, University of London; ISEA International; and Sabanci University, Istanbul.

Search engine content analysis

Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.

Peer to peer English/Chinese cross-language information retrieval

Peer to peer systems have been widely used in the internet. However, most of the peer to peer information systems are still missing some of the important features, for example cross-language IR (Information Retrieval) and collection selection / fusion features. Cross-language IR is the state-of-art research area in IR research community. It has not been used in any real world IR systems yet. Cross-language IR has the ability to issue a query in one language and receive documents in other languages. In typical peer to peer environment, users are from multiple countries. Their collections are definitely in multiple languages. Cross-language IR can help users to find documents more easily. E.g. many Chinese researchers will search research papers in both Chinese and English. With Cross-language IR, they can do one query in Chinese and get documents in two languages. The Out Of Vocabulary (OOV) problem is one of the key research areas in crosslanguage information retrieval. In recent years, web mining was shown to be one of the effective approaches to solving this problem. However, how to extract Multiword Lexical Units (MLUs) from the web content and how to select the correct translations from the extracted candidate MLUs are still two difficult problems in web mining based automated translation approaches. Discovering resource descriptions and merging results obtained from remote search engines are two key issues in distributed information retrieval studies. In uncooperative environments, query-based sampling and normalized-score based merging strategies are well-known approaches to solve such problems. However, such approaches only consider the content of the remote database but do not consider the retrieval performance of the remote search engine. This thesis presents research on building a peer to peer IR system with crosslanguage IR and advance collection profiling technique for fusion features. Particularly, this thesis first presents a new Chinese term measurement and new Chinese MLU extraction process that works well on small corpora. An approach to selection of MLUs in a more accurate manner is also presented. After that, this thesis proposes a collection profiling strategy which can discover not only collection content but also retrieval performance of the remote search engine. Based on collection profiling, a web-based query classification method and two collection fusion approaches are developed and presented in this thesis. Our experiments show that the proposed strategies are effective in merging results in uncooperative peer to peer environments. Here, an uncooperative environment is defined as each peer in the system is autonomous. Peer like to share documents but they do not share collection statistics. This environment is a typical peer to peer IR environment. Finally, all those approaches are grouped together to build up a secure peer to peer multilingual IR system that cooperates through X.509 and email system.

Velocity and Concentration field of discharge from a boat propeller

Two-stroke outboard boat engines using total loss lubrication deposit a significant proportion of their lubricant and fuel directly into the water. The purpose of this work is to document the velocity and concentration field characteristics of a submerged swirling water jet emanating from a propeller in order to provide information on its fundamental characteristics. Measurements of the velocity and concentration field were performed in a turbulent jet generated by a model boat propeller (0.02 m diameter) operating at 1500 rpm and 3000 rpm. The measurements were carried out in the Zone of Established Flow up to 50 propeller diameters downstream of the propeller. Both the mean axial velocity profile and the mean concentration profile showed self-similarity. Further, the stand deviation growth curve was linear. The effects of propeller speed and dye release location were also investigated.

Investigating customer click through behaviour with integrated sponsored and nonsponsored results

This paper reports findings from a study investigating the effect of integrating sponsored and nonsponsored search engine links into a single web listing. The premise underlying this research is that web searchers are chiefly interested in relevant results. Given the reported negative bias that web searchers have concerning sponsored links, separate listings may be a disservice to web searchers as it might not direct them to relevant websites. Some web meta-search engines integrate sponsored and nonsponsored links into a single listing. Using a web search engine log of over 7 million interactions from hundreds of thousands of users from a major web meta-search engine, we analysed the click-through patterns for both sponsored and nonsponsored links. We also classified web queries as informational, navigational and transactional based on the expected type of content and analysed the click-through patterns of each classification. The findings show that for more than 35% of queries, there are no clicks on any result. More than 80% of web queries are informational in nature and approximately 10% are transactional, and 10% navigational. Sponsored links account for approximately 15% of all clicks. Integrating sponsored and nonsponsored links does not appear to increase the clicks on sponsored listings. We discuss how these research results could enhance future sponsored search platforms.

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Analyzing web multimedia query reformulation behavior

Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems.

A study and comparison of multimedia Web searching : 1997-2006

Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.

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.

Determining the informational, navigational and transactional intent of web queries

In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.

Exploring young children's web searching and technoliteracy

Purpose – This paper aims to report findings from an exploratory study investigating the web interactions and technoliteracy of children in the early childhood years. Previous research has studied aspects of older children’s technoliteracy and web searching; however, few studies have analyzed web search data from children younger than six years of age. Design/methodology/approach – The study explored the Google web searching and technoliteracy of young children who are enrolled in a “preparatory classroom” or kindergarten (the year before young children begin compulsory schooling in Queensland, Australia). Young children were video- and audio-taped while conducting Google web searches in the classroom. The data were qualitatively analysed to understand the young children’s web search behaviour. Findings – The findings show that young children engage in complex web searches, including keyword searching and browsing, query formulation and reformulation, relevance judgments, successive searches, information multitasking and collaborative behaviours. The study results provide significant initial insights into young children’s web searching and technoliteracy. Practical implications – The use of web search engines by young children is an important research area with implications for educators and web technologies developers. Originality/value – This is the first study of young children’s interaction with a web search engine.

EUAustralia Online : News & Information from the Capitals of Europe to Australia (www.euaustralia.com)

Experimental / pilot online journalistic publication. EUAustralia Online (www.euaustralia.com) is a pilot niche publication identifying and demonstrating dynamics of online journalism. The editor, an experienced and senior journalist and academic, specialist in European studies, commenced publication on 28.8.06 during one year’s “industry immersion” -- with media accreditation to the European Commission, Brussels. Reporting now is from Australia and from Europe on field trip exercises. Student editors participate making it partly a training operation. EUAustralia demonstrates adaptation of conventional, universal, “Western” liberal journalistic practices. Its first premise is to fill a knowledge gap in Australia about the European Union -- institutions, functions and directions. The second premise is to test the communications capacity of the online format, where the publication sets a strong standard of journalistic credibility – hence its transparency with sourcing or signposting of “commentary” or ”opinion”. EUAustralia uses modified, enhanced weblog software allowing for future allocation of closed pages to subscribers. An early exemplar of its kind, with modest upload rate (2010-13 average, 16 postings monthly), esteemed, it commands over 180000 site visits p.a. (half as unique visitors; AWB Statistics); strongly rated by search engines, see page one Googlr placements for “EU Australia”. Comment by the ISP (SeventhVision, Broadbeach, Queensland): “The site has good search engine recognition because seen as credible; can be used to generate revenue”. This journalistic exercise has been analysed in theoretical context twice, in published refereed conference proceedings (Communication and Media Policy Forum, Sydney; 2007, 2009).