To design a useful recommender system, it is important to understand how products relate each other. For example, while user browsing mobile phones, might make sense recommend other but once they buy phone, we instead want batteries, cases, or chargers. In economics, these two types of recommendations are referred as substitutes and complements: that can be purchased other, complements in addition Such relationships essential help us identify items relevant user's search.

Abstract Social media has become an alternative communication mechanism for the public to reach out emergency services during time-sensitive events. However, information overload of social experienced by these services, coupled with their limited human resources, challenges them timely identify, prioritize, and organize critical requests help. In this paper, we first present a formal model serviceability called Social-EOC , which describes elements serviceable message posted in expressing...

The recent surge in women reporting sexual assault and harassment (e.g., #metoo campaign) has highlighted a longstanding societal crisis. This injustice is partly due to culture of discrediting who report such crimes also, rape myths 'women lie about rape'). Social web can facilitate the further proliferation deceptive beliefs through intentional messaging by malicious actors. multidisciplinary study investigates Twitter posts related assaults for characterizing types intent, which leads on...

Social media has become an integral part of our daily lives. During time-critical events, the public shares a variety posts on social including reports for resource needs, damages, and help offerings affected community. Such can be relevant may contain valuable situational awareness information. However, information overload challenges timely processing extraction by emergency services. Furthermore, growing usage multimedia content in recent years further adds to challenge mining from media....

End-to-End (E2E) automatic speech recognition (ASR) systems used in voice assistants often have difficulties recognizing infrequent words personalized to the user, such as names and places. Rare non-trivial pronunciations, cases, human knowledge form of a pronunciation lexicon can be useful. We propose PROnunCiation-aware conTextual adaptER (PROCTER) that dynamically injects into an RNN-T model by adding phonemic embedding along with textual embedding. The experimental results show proposed...

The task of recognition emotions from speech signals is one that has been going on for a long time. In the previous works, dominance prosodic and spectral features have observed when it comes to emotions. But signal also consists Source level information which gets lost during this process. work, we combined several with excitation source see how well model can perform emotion task. For in hand taken 3 databases namely, Berlin Emotional Database (Berlin Emo-DB), Surrey Audio-Visual Expressed...

Extensive research on social media usage during emergencies has shown its value to provide life-saving information, if a mechanism is in place filter and prioritize messages. Existing ranking systems can baseline for selecting which updates or alerts push emergency responders. However, prior not investigated depth how many often should these be generated, considering given bound the workload user due limited budget of attention this stressful work environment. This paper presents novel...

There is an increasing amount of information posted on Web, especially social media during real world events. Likewise, there a vast and opinions about humanitarian issues media. Mining such data can provide timely knowledge to inform disaster resource allocation for who needs what where as well policies causes. However, overload key challenge in leveraging this big organizations. We present interactive user-feedback based streaming analytics system `CitizenHelper-Adaptive' mine media, news,...

High-quality human annotations are necessary to create effective machine learning systems for social media. Low-quality indirectly contribute the creation of inaccurate or biased systems. We show that annotation quality is dependent on ordering instances shown annotators (referred as 'annotation schedule'), and can be improved by local changes in instance provided annotators, yielding a more accurate data stream efficient real-time media analytics. propose an error-mitigating active...

With the growing adoption of Internet and mobile technology, information exchange via social media has greatly influenced both government corporate operations. Social Media not only become a platform for mere entertainment communication but great source innovation public services. While millions users generate data on these platforms everyday, challenge is to effectively extract analyze from big in productive manner improving services future smart connected communities.

Although social media provides a vibrant platform to discuss real-world events, the quantity of information generated can overwhelm decision making based on that information. By better understanding who is participating in sharing, we more effectively filter as event unfolds. Fine-grained credible sources even help develop trusted network users for specific events or situations. Given culture relying actors work practices humanitarian and disaster response domain, propose identify potential...

The colloquium presents multiple perspectives on managing social organizations. Social organizations have emerged from not-for-profit They meet an important unfulfilled need of collective societal good. Some a strong legacy. There is no standard way governing/administring/managing management style needs to be context-specific. impact are also varied. Often the emphasis effectiveness rather than efficiency. articles draw experience founder/co-founder, managers and academicians who worked...

The bearing serves as a crucial element of any machinery with gearbox.It is essential to diagnose faults effectively ensure the machinery's safety and normal operation.Therefore, identification assessment mechanical in bearings are extremely significant for ensuring reliable operation.This comparative study shows performance fault diagnosis by utilizing various machine learning methodologies, including SVM, KNN, linear regression, ridge XGB AdaBoost cat boosting regression.Bearings like...

Effective labeled data collection plays a critical role in developing and fine-tuning robust streaming analytics systems. However, continuously labeling documents to filter relevant information poses significant challenges like limited budget or lack of high-quality labels. There is need for efficient human-in-the-loop machine learning (HITL-ML) design improve One particular HITL- ML approach online active learning, which involves iteratively selecting small set the most informative enhance...