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patriciaAlache
Faith and Victory Church 1302 A Street SE Auburn WA 98002 Services: Sunday 9 & 11 AM Wednesday 7 PM www.faithandvictory.com @FVChurchAuburn
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People search is an active research topic in recent years. Related works includes expert finding, collaborator recommendation, link prediction and social matching. However, the diverse objectives and exploratory nature of those tasks make it difficult to develop a flexible method for people search that works for every task. In this project, we developed PeopleExplorer, an interactive people search system to support exploratory search tasks when looking for people. In the system, users could specify their task objectives by selecting and adjusting key criteria. Three criteria were considered: the content relevance, the candidate authoritativeness and the social similarity between the user and the candidates. This project represents a first attempt to add transparency to exploratory people search, and to give users full control over the search process. The system was evaluated through an experiment with 24 participants undertaking four different tasks. The results show that with comparable time and effort, users of our system performed significantly better in their people search tasks than those using the baseline system. Users of our system also exhibited many unique behaviors in query reformulation and candidate selection. We found that users’ general perceptions about three criteria varied during different tasks, which confirms our assumptions regarding modeling task difference and user variance in people search systems.
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patriciaAlache
Faith and Victory Church 1302 A Street SE Auburn WA 98002 Services: Sunday 9 & 11 AM Wednesday 7 PM www.faithandvictory.com @FVChurchAuburn
122015 powerpoint wide screen
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People search is an active research topic in recent years. Related works includes expert finding, collaborator recommendation, link prediction and social matching. However, the diverse objectives and exploratory nature of those tasks make it difficult to develop a flexible method for people search that works for every task. In this project, we developed PeopleExplorer, an interactive people search system to support exploratory search tasks when looking for people. In the system, users could specify their task objectives by selecting and adjusting key criteria. Three criteria were considered: the content relevance, the candidate authoritativeness and the social similarity between the user and the candidates. This project represents a first attempt to add transparency to exploratory people search, and to give users full control over the search process. The system was evaluated through an experiment with 24 participants undertaking four different tasks. The results show that with comparable time and effort, users of our system performed significantly better in their people search tasks than those using the baseline system. Users of our system also exhibited many unique behaviors in query reformulation and candidate selection. We found that users’ general perceptions about three criteria varied during different tasks, which confirms our assumptions regarding modeling task difference and user variance in people search systems.
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Generative AI refers to a class of machine learning algorithms that are designed to generate new data samples that are similar to those in the training data. Unlike traditional AI models that are trained to recognize patterns and make predictions, generative AI models have the ability to create entirely new data based on the patterns they have learned. This is achieved through techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer architectures, among others.
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The presentation from our live stream where we shared insights from our new research into the 2024 Smart Building Startup Landscape. Memoori has seen a 33% Decrease in Funding Rounds Compared to the Previous Year. However, with $3.5 Billion invested in 2023 and over $2 Billion already invested in the first 4 months of 2024, the outlook for investment remains positive.
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In today's digital world, trust is key to customer relationships, but keeping it is a huge challenge. Customers are well-informed and empowered, quick to change brands if their trust is broken, even if it costs them more. This puts a lot of pressure on organizations to handle trust and safety issues with great care and transparency. The challenge, however, is real. Fragmented solutions have left privacy, legal, and security teams in a perpetual cycle of catch-up, struggling to update privacy notices, manage customer data rights, and answer lengthy security questionnaires—all while trying to prove ROI to the business. It's a thankless job, filled with repetition, tedious tasks, and constant interdepartmental coordination. Combine this with fast regulatory changes and the quick evolution of AI, and it becomes overwhelming. Join this webinar to learn more about TrustArc's new innovative solution Trust Center, the only unified, no-code online hub for trust and safety information built for privacy, security, compliance, and legal teams. Trust Center streamlines your path to compliance, shortens the pre-sales cycle, and reduces both legal and regulatory risks, saving time, effort, and cost. This webinar will review: - Why companies are building unified Trust Centers for a robust privacy program. - How unified Trust Centers streamline sales cycles, ensure regulatory compliance, and reduce operational bottlenecks. - How compliance, legal, security, GRC, and privacy teams benefit from a unified Trust Center in terms of needs, pains, and outcomes. - How TrustArc Trust Center saves time and work while reducing legal, reputational, and compliance risk by effectively managing policies, notices, terms, and disclosures, and providing real-time updates on subprocessors.
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Discover the top CodeIgniter development companies that can elevate your project to new heights. Our blog explores the best firms known for their expertise in CodeIgniter framework development. From robust web applications to scalable solutions, these companies deliver excellence. Whether you're a startup or an enterprise, find the perfect match for your development needs on Top CSS Gallery's blog.
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Because observability is such a broad topic – and often something we learn on the job – it can feel like there’s too much to learn at once. But you don’t have to tackle everything and can start with the basics and build from there! Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack. No matter what tooling is in place, there are still observability fundamentals that developers should know. That’s why I’ve put together a primer on the different telemetry types, when to use them, how to understand the data journey, and what to look for in time series graphs.
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Generative AI refers to a class of machine learning algorithms that are designed to generate new data samples that are similar to those in the training data. Unlike traditional AI models that are trained to recognize patterns and make predictions, generative AI models have the ability to create entirely new data based on the patterns they have learned. This is achieved through techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer architectures, among others.
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In today's digital world, trust is key to customer relationships, but keeping it is a huge challenge. Customers are well-informed and empowered, quick to change brands if their trust is broken, even if it costs them more. This puts a lot of pressure on organizations to handle trust and safety issues with great care and transparency. The challenge, however, is real. Fragmented solutions have left privacy, legal, and security teams in a perpetual cycle of catch-up, struggling to update privacy notices, manage customer data rights, and answer lengthy security questionnaires—all while trying to prove ROI to the business. It's a thankless job, filled with repetition, tedious tasks, and constant interdepartmental coordination. Combine this with fast regulatory changes and the quick evolution of AI, and it becomes overwhelming. Join this webinar to learn more about TrustArc's new innovative solution Trust Center, the only unified, no-code online hub for trust and safety information built for privacy, security, compliance, and legal teams. Trust Center streamlines your path to compliance, shortens the pre-sales cycle, and reduces both legal and regulatory risks, saving time, effort, and cost. This webinar will review: - Why companies are building unified Trust Centers for a robust privacy program. - How unified Trust Centers streamline sales cycles, ensure regulatory compliance, and reduce operational bottlenecks. - How compliance, legal, security, GRC, and privacy teams benefit from a unified Trust Center in terms of needs, pains, and outcomes. - How TrustArc Trust Center saves time and work while reducing legal, reputational, and compliance risk by effectively managing policies, notices, terms, and disclosures, and providing real-time updates on subprocessors.
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Because observability is such a broad topic – and often something we learn on the job – it can feel like there’s too much to learn at once. But you don’t have to tackle everything and can start with the basics and build from there! Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack. No matter what tooling is in place, there are still observability fundamentals that developers should know. That’s why I’ve put together a primer on the different telemetry types, when to use them, how to understand the data journey, and what to look for in time series graphs.
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