A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation

Recommending a ranked list of interesting venues to users based on their preferences has become a key functionality in Location-Based Social Networks (LBSNs) such as Yelp and Gowalla. Bayesian Personalised Ranking (BPR) is a popular pairwise recommendation technique that is used to generate the ranked list of venues of interest to a user, by leveraging the user's implicit feedback such as their check-ins as instances of positive feedback, while randomly sampling other venues as negative instances. To alleviate the sparsity that affects the usefulness of recommendations by BPR for users with few check-ins, various approaches have been proposed in the literature to incorporate additional sources of information such as the social links between users, the textual content of comments, as well as the geographical location of the venues. However, such approaches can only readily leverage one source of additional information for negative sampling. Instead, we propose a novel Personalised Ranking Framework with Multiple sampling Criteria (PRFMC) that leverages both geographical influence and social correlation to enhance the effectiveness of BPR. In particular, we apply a multi-centre Gaussian model and a power-law distribution method, to capture geographical influence and social correlation when sampling negative venues, respectively. Finally, we conduct comprehensive experiments using three large-scale datasets from the Yelp, Gowalla and Brightkite LBSNs. The experimental results demonstrate the effectiveness of fusing both geographical influence and social correlation in our proposed PRFMC framework and its superiority in comparison to BPR-based and other similar ranking approaches. Indeed, our PRFMC approach attains a 37% improvement in MRR over a recently proposed approach that identifies negative venues only from social links

Dynamic Matrix Factorization with Priors on Unknown Values

Advanced and effective collaborative filtering methods based on explicit feedback assume that unknown ratings do not follow the same model as the observed ones (\emph{not missing at random}). In this work, we build on this assumption, and introduce a novel dynamic matrix factorization framework that allows to set an explicit prior on unknown values. When new ratings, users, or items enter the system, we can update the factorization in time independent of the size of data (number of users, items and ratings). Hence, we can quickly recommend items even to very recent users. We test our methods on three large datasets, including two very sparse ones, in static and dynamic conditions. In each case, we outrank state-of-the-art matrix factorization methods that do not use a prior on unknown ratings.Comment: in the Proceedings of 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining 201

Behaviour and enclosure use of captive parma wallabies (Macropus parma): an assessment of compatibility within a mixed-species exhibit

Many zoos choose to house parma wallabies (Macropus parma) in mixed-species exhibits and a successful combination of species can provide a source of enrichment. However, there are potential health and welfare concerns, so it is important to consider species compatibility. This study investigates the effects of mixed-species housing on the parma wallaby. Parma wallabies at Dudley Zoological Gardens were observed for nine days in two different housing systems: mixed species (MS), with Patagonian mara (Dolichotis patagonum), and single species (SS). Scan sampling of all individuals, across a range of behaviours, was carried out for 90 minutes across the day. Differences in foraging behaviour were observed, with wallabies housed in the MS exhibit foraging significantly less than the SS group (W27=899.0, P<0.01). Wallabies in the MS enclosure performed a novel behaviour, agonistic directional urination that was not observed in the SS group. Enclosure use was analysed using a Spread of Participation Index (SPI); values revealed MS wallabies utilised less of their enclosure, with a notable preference for areas not frequented by the mara (W27=899.0, P<0.05). The results suggest that the MS wallabies are affected by the presence of the mara, both behaviourally and in enclosure use, which could be indicative of a negative welfare state. This study provides evidence of species incompatibility, a potential issue for the welfare of captive parma wallabies and the successful maintenance of this species in captivity. Careful and continual monitoring of species within mixed-species enclosures is recommended

Knowledge-aware Complementary Product Representation Learning

Learning product representations that reflect complementary relationship plays a central role in e-commerce recommender system. In the absence of the product relationships graph, which existing methods rely on, there is a need to detect the complementary relationships directly from noisy and sparse customer purchase activities. Furthermore, unlike simple relationships such as similarity, complementariness is asymmetric and non-transitive. Standard usage of representation learning emphasizes on only one set of embedding, which is problematic for modelling such properties of complementariness. We propose using knowledge-aware learning with dual product embedding to solve the above challenges. We encode contextual knowledge into product representation by multi-task learning, to alleviate the sparsity issue. By explicitly modelling with user bias terms, we separate the noise of customer-specific preferences from the complementariness. Furthermore, we adopt the dual embedding framework to capture the intrinsic properties of complementariness and provide geometric interpretation motivated by the classic separating hyperplane theory. Finally, we propose a Bayesian network structure that unifies all the components, which also concludes several popular models as special cases. The proposed method compares favourably to state-of-art methods, in downstream classification and recommendation tasks. We also develop an implementation that scales efficiently to a dataset with millions of items and customers

Communication from the zoo: Reports from zoological facilities of the impact of COVID-19 closures on animals

Zoos engaged in a range of communication types with prospective visitors during the temporary closures necessitated by the COVID-19 pandemic. This study sought to (1) investigate social media reports and public responses to zoo-animal-related posts over a one-year period during COVID-19 lockdowns; (2) understand the use of reporting language in news articles concerning animal responses during zoo closures, and to investigate whether this differed across species; and (3) investigate how keepers perceived general animal behavior, and how they perceived animal behavior in keeper–animal interactions, during the COVID-19 facility closures. Data were collected from BIAZA-accredited zoos’ Facebook pages (March 2020 to March 2021) and news reports (Google search outputs from 20 March to 5 April 2021). Keeper perceptions were captured via questionnaires (May to August 2021). Data were collected on taxa, the reported behavioral changes and the language used in media communications. In Facebook posts and news reports, mammals were more frequently represented than was expected (p < 0.05). Behavioral responses were more frequently negative (p < 0.05) and less frequently positive or neutral (p < 0.05). Keepers reported overall behavioral changes, as well as changes during their own interactions with animals. On Facebook, mammals were described using a combination of behavioral descriptions and anthropomorphic terms, which were used more frequently than was expected (p < 0.05). In the news reports concerning primate species, anthropomorphic descriptions were used more frequently than expected (p < 0.05), while behavioral descriptions were used less frequently than expected (p < 0.05). The reports regarding the Carnivora were the reverse of this. This study enabled an understanding of the impact of the temporary closures on the animals, and how this impact was communicated to the public. The findings may reflect the relationships that humans have with animals and the need for communication methods that will capture visitors’ interest and induce empathy with the various species

TPR: Text-aware Preference Ranking for recommender systems

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Impacts of COVID-19 on animals in zoos: a longitudinal multi-species analysis

Prolonged and repetitive COVID-19 facility closures have led to an abrupt cessation of visitors within UK and Irish zoos for variable periods since March 2020. This study sought to increase understanding of the impact of closures and reopenings on animal behaviour, thereby broadening understanding of whether zoo animals habituate to visitors. Data were collected from June to August 2020 at two UK facilities on eight species (n = 1 Chinese goral, n = 2 Grevy’s zebra, n = 11 swamp wallaby, n = 2 Rothschild’s giraffe, n = 2 nyala, n = 4 Chapman’s zebra, n = 2 snow leopard and n = 3 Amur leopard). Behaviour change and enclosure use was variable across species but most changes were non-significant. Grevy’s zebra engaged in more comfort behaviour during closure periods than post-closure (p < 0.05). Chinese goral engaged in more environmental interactions during closure periods (p < 0.05). Grevy’s zebra spent longer than would be expected by chance closest to public viewing areas during closure periods (p < 0.008). These results suggest variable impacts of covid-19 closures and reopenings, mirroring human-animal interaction literature. We highlight the potential for some species to take longer to re-habituate to the presence of zoo visitors. As facility closures/reopenings are ongoing, we advocate a longitudinal monitoring approach. Furthermore, we recommend incorporation of physical and physiological measures of welfare where possible, alongside behavioural responses, to enable a holistic approach to answering fundamental questions on whether zoo animals habituate to visitors

Prevalence of macropod progressive periodontal disease ("lumpy jaw") in wild western grey kangaroos (Macropus fuliginosus)

Macropod Progressive Periodontal Disease (MPPD), colloquially referred to as “lumpy jaw”, is a commonly observed disease in captive macropods. However, the prevalence of this disease in the wild is largely unknown. A systematic study of MPPD in wild macropods would provide an indication of the endemic presence of this disease in wild populations, and could assist those managing disease in captive populations, by highlighting potential risk factors for disease development. Utilising kangaroos culled as part of a population management program, this study used visual observation and computer tomography (CT) of skulls to investigate the prevalence of MPPD in wild western grey kangaroos (Macropus fuliginosus) from the Perth metropolitan region, Western Australia. The sample suitable for visual and CT analysis comprised 121 specimens, 71 (58.7%) male and 50 (41.3%) female, with the mean age for all 121 specimens being 4.5 years (±2.63 SD). No evidence of MPPD was detected in any of the specimens examined. Overabundance may not be associated with the development of MPPD, as previously considered, and age-related factors should not be eliminated. This results may reflect low susceptibility to MPPD in western grey kangaroos, given low prevalence is reported in this species in captive populations. Further investigation into species-specificity is recommended, and should include samples with soft tissue to improve sensitivity of disease detection. Surveillance of MPPD in wild populations of macropods helps to improve our understanding of the biological significance, development and potential spread of this disease. Notably, this information may assist in the management of MPPD in captive populations, and may have a positive impact on both the welfare and conservation of macropods in captivity