A hybrid recommender systems based on weighted tags

Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.

Massively parallel sequencing and analysis of expressed sequence tags in a successful invasive plant

Background Invasive species pose a significant threat to global economies, agriculture and biodiversity. Despite progress towards understanding the ecological factors associated with plant invasions, limited genomic resources have made it difficult to elucidate the evolutionary and genetic factors responsible for invasiveness. This study presents the first expressed sequence tag (EST) collection for Senecio madagascariensis, a globally invasive plant species. Methods We used pyrosequencing of one normalized and two subtractive libraries, derived from one native and one invasive population, to generate an EST collection. ESTs were assembled into contigs, annotated by BLAST comparison with the NCBI non-redundant protein database and assigned gene ontology (GO) terms from the Plant GO Slim ontologies. Key Results Assembly of the 221 746 sequence reads resulted in 12 442 contigs. Over 50 % (6183) of 12 442 contigs showed significant homology to proteins in the NCBI database, representing approx. 4800 independent transcripts. The molecular transducer GO term was significantly over-represented in the native (South African) subtractive library compared with the invasive (Australian) library. Based on NCBI BLAST hits and literature searches, 40 % of the molecular transducer genes identified in the South African subtractive library are likely to be involved in response to biotic stimuli, such as fungal, bacterial and viral pathogens. Conclusions This EST collection is the first representation of the S. madagascariensis transcriptome and provides an important resource for the discovery of candidate genes associated with plant invasiveness. The over-representation of molecular transducer genes associated with defence responses in the native subtractive library provides preliminary support for aspects of the enemy release and evolution of increased competitive ability hypotheses in this successful invasive. This study highlights the contribution of next-generation sequencing to better understanding the molecular mechanisms underlying ecological hypotheses that are important in successful plant invasions.

Mobile banking customization via user-defined tags

In this paper, we describe on-going work on mobile banking customization, particularly in the Australian context. The use of user-defined tags to facilitate personalized interactions in the mobile context is explored. The aim of this research is to find ways to improve mobile banking interaction. Customization is more significant in the mobile context than online due to factors such as smaller screen sizes and limited software and hardware capabilities, placing an increased emphasis on usability. This paper explains how user-defined tags can aid different types of customization at the interaction level. A preliminary prototype has been developed to demonstrate the mechanics of the proposed approach. Potential implications, design decisions and limitations are discussed with an outline of future work.

Minimizing information leakage of tree-based RFID authentication protocols using alternate tree-walking

The privacy of efficient tree-based RFID authentication protocols is heavily dependent on the branching factor on the top layer. Indefinitely increasing the branching factor, however, is not a viable option. This paper proposes the alternate-tree walking scheme as well as two protocols to circumvent this problem. The privacy of the resulting protocols is shown to be comparable to that of linear-time protocols, where there is no leakage of information, whilst reducing the computational load of the database by one-third of what is required of tree-based protocols during authentication. We also identify and address a limitation in quantifying privacy in RFID protocols.

Identifying customer behaviour and dwell time using soft biometrics

In a commercial environment, it is advantageous to know how long it takes customers to move between different regions, how long they spend in each region, and where they are likely to go as they move from one location to another. Presently, these measures can only be determined manually, or through the use of hardware tags (i.e. RFID). Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. They include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. While these traits cannot provide robust authentication, they can be used to provide identification at long range, and aid in object tracking and detection in disjoint camera networks. In this chapter we propose using colour, height and luggage soft biometrics to determine operational statistics relating to how people move through a space. A novel average soft biometric is used to locate people who look distinct, and these people are then detected at various locations within a disjoint camera network to gradually obtain operational statistics

Personalized recommender systems integrating tags and item taxonomy

The social tags in Web 2.0 are becoming another important information source to profile users' interests and preferences to make personalized recommendations. To solve the problem of low information sharing caused by the free-style vocabulary of tags and the long tails of the distribution of tags and items, this paper proposes an approach to integrate the social tags given by users and the item taxonomy with standard vocabulary and hierarchical structure provided by experts to make personalized recommendations. The experimental results show that the proposed approach can effectively improve the information sharing and recommendation accuracy.

Improving the efficiency of RFID authentication with pre-computation

Security of RFID authentication protocols has received considerable interest recently. However, an important aspect of such protocols that has not received as much attention is the efficiency of their communication. In this paper we investigate the efficiency benefits of pre-computation for time-constrained applications in small to medium RFID networks. We also outline a protocol utilizing this mechanism in order to demonstrate the benefits and drawbacks of using thisapproach. The proposed protocol shows promising results as it is able to offer the security of untraceableprotocols whilst only requiring the time comparable to that of more efficient but traceable protocols.

A state-aware RFID privacy model with reader corruption

A number of security models have been proposed for RFID systems. Recent studies show that current models tend to be limited in the number of properties they capture. Consequently, models are commonly unable to distinguish between protocols with regard to finer privacy properties. This paper proposes a privacy model that introduces previously unavailable expressions of privacy. Based on the well-studied notion of indistinguishability, the model also strives to be simpler, easier to use, and more intuitive compared to previous models.

A state-aware RFID privacy model with reader corruption

A number of security models have been proposed for RFID systems. Recent studies show that current models tend to be limited in the number of properties they capture. Consequently, models are commonly unable to distinguish between protocols with regard to finer privacy properties. This paper proposes a privacy model that introduces previously unavailable expressions of privacy. Based on the well-studied notion of indistinguishability, the model also strives to be simpler, easier to use, and more intuitive compared to previous models.

Privacy of RFID - models and protocols

Radio Frequency Identification is a wireless identification method that utilizes the reception of electromagnetic radio waves. This research has proposed a novel model to allow for an in-depth security analysis of current protocols and developed new flexible protocols that can be adapted to offer either stronger security or better efficiency.