Venue category recommendation is an essential application for the tourism and advertisement industries, wherein it may suggest attractive localities within close proximity to users’ current location. Considering that many adults use more than three social networks simultaneously, it is reasonable to leverage on this rapidly growing multi-source social media data to boost venue recommendation performance. Another approach to achieve higher recommendation results is to utilize group knowledge, which is able to diversify recommendation output. Taking into account these two aspects, we introduce a novel cross-network collaborative recommendation framework C 3R, which utilizes both individual and group knowledge, while being trained on data from multiple social media sources. Group knowledge is derived based on new crosssource user community detection approach, which utilizes both inter-source relationship and the ability of sources to complement each other. To fully utilize multi-source multi-view data, we process user-generated content by employing state-of-the-art text, image, and location processing techniques. Our experimental results demonstrate the superiority of our multi-source framework over state-of-the-art baselines and different data source combinations. In addition, we suggest a new approach for automatic construction of inter-network relationship graph based on the data, which eliminates the necessity of having pre-defined domain knowledge
In this technical demonstration, we showcase the first ai-driven social multimedia influencer discovery marketplace, called SoMin. The platform combines advanced data analytics and behavioral science to help marketers find, understand their audience and engage the most relevant social media micro-influencers at a large scale. SoMin harvests brand-specific life social multimedia streams in a specified market domain, followed by rich analytics and semantic-based influencer search. The Individual User Profiling models extrapolate the key personal characteristics of the brand audience, while the influencer retrieval engine reveals the semantically-matching social media influencers to the platform users. The influencers are matched in terms of both their-posted content and social media audiences, while the evaluation results demonstrate an excellent performance of the proposed recommender framework. By leveraging influencers at a large scale, marketers will be able to execute more effective marketing campaigns of higher trust and at a lower cost.
The exponential growth of online social networks has inspired us to tackle the problem of individual user attributes inference from the Big Data perspective. It is well known that various social media networks exhibit different aspects of user interactions, and thus represent users from diverse points of view. In this preliminary study, we make the first step towards solving the significant problem of personality profiling from multiple social networks. Specifically, we tackle the task of relationship prediction, which is closely related to our desired problem. Experimental results show that the incorporation of multi-source data helps to achieve better prediction performance as compared to single-source baselines.
When setting out on a journey, it’s always wise to have a reliable roadmap. The same holds true when it comes to embarking on new tech projects and initiatives. And just as there’s considerable flexibility in terms of routes and guides when planning a trip, tech leaders and project managers have several choices when it comes to tools and techniques for plotting and refining a project roadmap.
With so many options available, a young tech leader or first-time project manager can benefit from the advice and experience of seasoned industry leaders. Below, 15 members of Forbes Technology Council share some roadmapping tools and techniques they’ve found effective and why they work so well.
While there’s more focus than ever on providing a good user interface/user experience in new tech tools, that doesn’t just mean adding lots of “wow” functionality. To ensure the best UX, it’s important for hardware and software developers to also pay attention to ergonomic design. A focus on ergonomics ensures that the tool is adapted to foster comfort and convenience for the human user—that is, the human should inform how the tool works, not the other way around.
While the concept is simple enough, implementing it can be challenging, as designers must take account of factors ranging from device sizes to color palettes. Here, 16 members of Forbes Technology Council share tips to help developers ensure they’ve incorporated good ergonomic design principles in their products.
A digital twin is precisely what its name suggests: A digital copy of a physical object or system—even a human being. It may be a simple concept, but the potential applications are anything but. Through the ongoing collection and exchange of data, a digital twin can simulate and even predict the behaviors and reactions of its physical twin in a variety of conditions, providing invaluable insights to industries ranging from manufacturing to healthcare.
Digital twin technology allows businesses and organizations to test products and processes, study and predict how real-world conditions can affect physical objects and beings, and make well-informed, big-impact decisions with minimized financial and human safety risks. Below, 16 members of Forbes Technology Council share some of the fascinating ways industries and organizations are leveraging digital twin technology.