A Factored Relevance Model for Contextual Point-of-Interest Recommendation

The challenge of providing personalized and contextually appropriate recommendations to a user is faced in a range of use-cases, e.g., recommendations for movies, places to visit, articles to read etc. In this paper, we focus on one such application, namely that of suggesting 'points of interest' (POIs) to a user given her current location, by leveraging relevant information from her past preferences. An automated contextual recommendation algorithm is likely to work well if it can extract information from the preference history of a user (exploitation) and effectively combine it with information from the user's current context (exploration) to predict an item's 'usefulness' in the new context. To balance this trade-off between exploration and exploitation, we propose a generic unsupervised framework involving a factored relevance model (FRLM), comprising two distinct components, one corresponding to the historical information from past contexts, and the other pertaining to the information from the local context. Our experiments are conducted on the TREC contextual suggestion (TREC-CS) 2016 dataset. The results of our experiments demonstrate the effectiveness of our proposed approach in comparison to a number of standard IR and recommender-based baselines

Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval

With the improvements in speech recognition and voice generation technologies over the last years, a lot of companies have sought to develop conversation understanding systems that run on mobile phones or smart home devices through natural language interfaces. Conversational assistants, such as Google Assistant and Microsoft Cortana, can help users to complete various types of tasks. This requires an accurate understanding of the user's information need as the conversation evolves into multiple turns. Finding relevant context in a conversation's history is challenging because of the complexity of natural language and the evolution of a user's information need. In this work, we present an extensive analysis of language, relevance, dependency of user utterances in a multi-turn information-seeking conversation. To this aim, we have annotated relevant utterances in the conversations released by the TREC CaST 2019 track. The annotation labels determine which of the previous utterances in a conversation can be used to improve the current one. Furthermore, we propose a neural utterance relevance model based on BERT fine-tuning, outperforming competitive baselines. We study and compare the performance of multiple retrieval models, utilizing different strategies to incorporate the user's context. The experimental results on both classification and retrieval tasks show that our proposed approach can effectively identify and incorporate the conversation context. We show that processing the current utterance using the predicted relevant utterance leads to a 38% relative improvement in terms of nDCG@20. Finally, to foster research in this area, we have released the dataset of the annotations.Comment: To appear in ACM CHIIR 2020, Vancouver, BC, Canad

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

The global burden of adolescent and young adult cancer in 2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. Methods Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. Findings There were 1.19 million (95% UI 1.11-1.28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59.6 [54.5-65.7] per 100 000 person-years) and high-middle SDI countries (53.2 [48.8-57.9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14.2 [12.9-15.6] per 100 000 person-years) and middle SDI (13.6 [12.6-14.8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23.5 million (21.9-25.2) DALYs to the global burden of disease, of which 2.7% (1.9-3.6) came from YLDs and 97.3% (96.4-98.1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally. Interpretation Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Neural Endorsement Based Contextual Suggestion

International audienc

Where To Go Next?: Exploiting Behavioral User Models in Smart Environments

There is a growing interest in using the Internet of Things (IoT) to create smart environments, which hold the promise to provide personalized experience based on the trail of user interactions with smart devices. We experiment with behavioral user models based on interactions with smart devices in a museum, and investigate the personalized recommendation of what to see after visiting an initial set of Point of Interests (POIs), a key problem in personalizing museum visits or tour guides. We have logged users' onsite physical information interactions of visits in a museum. Moreover, to have a better understanding of users' information interaction behaviors and their preferences, we have collected and studied query logs of a search engine of the same collection, and we have found similarities between users' online digital and onsite physical information interaction behaviors. We exploit user modeling based on users' different information interaction behaviors and experiment with a novel approach to a critical one-shot POI recommendation using deep neural multilayer perceptron based on explicitly given users' contextual information, and set-based extracted features using users' physical information interaction behaviors and similar users' digital information interaction behaviors. Experimental results indicates that our proposed behavioral user modeling, using both physical and digital user information interaction behaviors, improves the onsite POI recommendation baselines' performances in all common Information Retrieval evaluation metrics. Our proposed approach provides an effective way to achieve a high precision at rank 1 in onsite critical one-shot POI recommendation problem

On the Reusability of Open Test Collections

Creating test collections for modern search tasks is increas-ingly more challenging due to the growing scale and dy-namic nature of content, and need for richer contextualiza-tion of the statements of request. To address these issues, the TREC Contextual Suggestion Track explored an open test collection, where participants were allowed to submit any web page as a result for a personalized venue recom-mendation task. This prompts the question on the reus-ability of the resulting test collection: How does the open nature affect the pooling process? Can participants reliably evaluate variant runs with the resulting qrels? Can other teams evaluate new runs reliably? In short, does the set of pooled and judged documents effectively produce a post hoc test collection? Our main findings are the following: First, while there is a strongly significant rank correlation, the ef-fect of pooling is notable and results in underestimation of performance, implying the evaluation of non-pooled systems should be done with great care. Second, we extensively ana-lyze impacts of open corpus on the fraction of judged docu-ments, explaining how low recall affects the reusability, and how the personalization and low pooling depth aggravate that problem. Third, we outline a potential solution by de-riving a fixed corpus from open web submissions

Synergistic effects of hydro extract of jujube fruit in combination with Mesalazine (orally) and Asacol (intra-colonic) administration in ameliorating animal model of ulcerative colitis

This study was done to investigate the synergistic impacts hydro extract of jujube fruit in combination with Mesalazine (orally) and Asacol (intra-colonic) administration in ameliorating animal model of ulcerative colitis (UC). After the induction of UC and with the development of signs, the treatment groups daily received the hydro extract of jujube fruit (200 mg/kg, orally, enema), Mesalazine (30 mg/kg, orally) and Asacol (10 mg/kg, enema). After 10 days, rats were euthanized and were studied. Findings indicated a significant increase in Myeloperoxidase (161.66 ± 10.40), Nitric oxide (216.01 ± 17.55), IL-6 (138.54 ± 7.02), and TNF-α (123.87 ± 9.80) colon tissue levels and pathological damage of positive control group compared with the negative control group. Hydro extract of jujube fruit in combination with Mesalazine (orally) and Asacol (intra-colonic) group represented a higher capability in significantly decreasing Myeloperoxidase (73.33 ± 9.07), Nitric oxide (81.66 ± 10.50), IL-6 (51.69 ± 5.19), TNF-α (30.59 ± 5.50) levels and pathological damage in compared with the other treatment groups. Considering accessibility and affordability of jujube fruit and the side effects of routine drugs, taking a combination of jujube fruit with low doses of routine pharmaceutical drugs can improve and cure ulcerative colitis disease. Resumo: Este estudo foi realizado para investigar os impactos sinérgicos do extrato aquoso do fruto da jujuba em combinação com a administração de Mesalazina (por via oral) e Asacol (intracolônico) na melhora do modelo animal de colite ulcerativa. Após a indução da colite ulcerativa e com o desenvolvimento de sinais, os grupos de tratamento receberam diariamente o extrato aquoso do fruto da jujuba (200 mg/kg, via oral, enema), Mesalazina (30 mg/kg, via oral) e Asacol (10 mg/kg, enema). Após 10 dias, os ratos foram eutanasiados e estudados. Os achados indicaram um aumento significativo dos níveis de mieloperoxidase (161,66 ± 10,40), óxido nítrico (216,01 ± 17,55), IL-6 (138,54 ± 7,02) e TNF-α (123,87 ± 9,80) no tecido do cólon e dano patológico do grupo controle positivo comparado com o grupo controle negativo. O extrato aquoso da fruta de jujuba em combinação com Mesalazina (oral) e Asacol (intracolônico) representou maior capacidade de redução significativa dos níveis de mieloperoxidase (73,33 ± 9,07), óxido nítrico (81,66 ± 10,50), IL-6 (51,69 ± 5,19), TNF-α (30,59 ± 5,50) e dano patológico em comparação com os outros grupos de tratamento. Considerando a acessibilidade e disponibilidade do fruto da jujuba e dos efeitos colaterais dos medicamentos de rotina, tomar uma combinação de jujuba com baixas doses de medicamentos farmacêuticos de rotina pode melhorar e curar a colite ulcerativa. Keywords: Colitis, Acetic acid, hydro extract jujube fruit, Palavras-chave: Colite, Ácido acético, Extrato aquoso da fruta da jujub

"Hi! I am the Crowd Tasker" - Crowdsourcing through Digital Voice Assistants

Inspired by the increasing prevalence of digital voice assistants, we demonstrate the feasibility of using voice interfaces to deploy and complete crowd tasks. We have developed Crowd Tasker, a novel system that delivers crowd tasks through a digital voice assistant. In a lab study, we validate our proof-ofconcept and show that crowd task performance through a voice assistant is comparable to that of a web interface for voicecompatible and voice-based crowd tasks for native English speakers. We also report on a field study where participants used our system in their homes. We find that crowdsourcing through voice can provide greater flexibility to crowd workers by allowing them to work in brief sessions, enabling multitasking, and reducing the time and effort required to initiate tasks. We conclude by proposing a set of design guidelines for the creation of crowd tasks for voice and the development of future voice-based crowdsourcing systems