Information Retrieval

Possible Applications of AI in HR Hppy


HR management personnel work with the latest HR tools to track a candidate's journey through the interview process. Smart badges collect relevant information such as dialogues between employees, networks in the company, where people spend their time, interactions, etc. New technology enables HR professional to measure things like effectiveness, efficiency, and employee experience by analyzing hiring decisions, personal development, and overall team climate. Although some HR departments utilize AI in their decision making processes, the technology still needs to be developed to the full extent.

Why you need to invest in search engine optimization ( ZDNet Academy)


That's the basis of search engine optimization (SEO), a targeted plan of attack to draw visitors to your site. With such a small window, optimizing your website to match commonly searched keywords and phrases can lead to increased traffic, and in turn, increased sales. Additionally, PPC refers to advertising on content sites via "banner ads" (i.e. With Serpstat, you not only get access to your own website's ranking within a keyword index, but the ranking of the top 100 domains in that index.

The future of search engines: Researchers combine artificial intelligence, crowdsourcing and supercomputers


This week, at the Annual Meeting of the Association for Computational Linguistics in Vancouver, Canada, Lease and collaborators from UT Austin and Northeastern University presented two papers describing their novel IR systems. They proposed a method for exploiting these existing linguistic resources via weight sharing to improve NLP models for automatic text classification. "This provides a general framework for codifying and exploiting domain knowledge in data-driven neural network models," say Byron Wallace, Lease's collaborator from Northeastern University. By improving core natural language processing technologies for automatic information extraction and the classification of texts, web search engines built on these technologies can continue to improve.

Web Page Ranking using Machine Learning


Example- List of URLS listed for a search query in search engine Experiments are conducted using real web services datasets and the outcome of the experiments using machine learning confirms an improvement over existing methods in Page Ranking. Let X {xi} be a collection of feature vectors (typically, a feature is any real valued number), and Y {yi} be a collection of associated classes, where yi is the class of the object described by feature vector xi. Page Ranking Reports · Domain Age Report · Title tag Report · Keyword Density Report · Keyword Meta tag Report · Description Meta tag Report · Body Text Report · In page Link Report · Link Popularity Report · Outbound Link Report · IMG ALT Attribute Report · Server Speed · Page Rank Report 28. Example- List of URLS listed for a search query in search engine Experiments are conducted using real web services datasets and the outcome of the experiments using machine learning confirms an improvement over existing methods in Page Ranking.

Implementing kd-tree for fast range-search, nearest-neighbor search and k-nearest-neighbor search algorithms in 2D in Java and python


The following figure shows the result of the range search algorithm on the same dataset after the 2d-tree is grown. The next animations show the nearest neighbor search algorithm for a given query point(the fixed white point with black border: the point (0.3, 0.9)) and how the the branches are traversed and the points (nodes) are visited in the 2-d-tree until the nearest neighbor is found. As can be seen from the next figure, the time complexity of 2-d tree building (insertion), nearest neighbor search and k-nearest neighbor query depend not only on the size of the datasets but also on the geometry of the datasets. The flocking boids simulator is implemented with 2-d-trees and the following 2 animations (java and python respectively) shows how the flock of birds fly together, the black / white ones are the boids and the red one is the predator hawk.

Bing Image Search Gets a Machine Learning Boost


Microsoft's search engine has gained the ability to automatically detect objects within a photo online, the company announced on Sept. 12. Using machine learning, image recognition and other artificial intelligence (AI) technologies, Bing Visual Search can automatically detect items and selects them for the user. On Aug. 1, Google peeled back the curtain on its efforts to weed out terror videos on YouTube using machine learning. The cloud file storage and collaboration company announced on Aug. 17 that it was employing Google Cloud Vision's image recognition capabilities to add a layer of intelligence to its repositories of enterprise content.

Google appeals against EU's €2.4bn fine over search engine results

The Guardian

Google is appealing against the record €2.4bn (£2.2bn) fine imposed by the European Union for its abuse of its dominance of the search engine market in building its shopping comparison service. In June, the EU official in charge of competition policy, commissioner Margrethe Vestager, told reporters that Google, a unit of US parent company Alphabet, had artificially and illegally promoted its own price comparison service in searches, denied both its consumers real choice and rival firms the ability to compete on a level playing field. And most importantly, it denied European consumers a genuine choice of services and the full benefits of innovation." Lobby group FairSearch, whose members include Google rivals such as British shopping comparison site Foundem and US travel site TripAdvisor, said the EU decision was sound.

How AI is revolutionizing recruiting and hiring


Accuracy is also important; being able to evaluate the precision (the fraction of received information that's relevant) and recall (the fraction of relevant information that's received) of algorithms can help sourcing and recruiting professionals make sure they're delivering the right candidates, she says. Some forward-thinking recruiters and hiring managers are using AI and machine learning to reverse-engineer candidate "fit," and to predict a potential candidate's performance in the role, says Chris Nicholson, CEO of artificial intelligence software company Skymind. So, the smartest recruiters and hiring managers would start gathering résumés, performance reviews, work product, any information at all about highly successful people that already work for them and plug that into an algorithm to figure out what you are looking for," Nicholson says. But using AI and machine learning can help unearth candidates missed by traditional screening, sourcing and recruiting methods.

Software Engineer II


Title: Software Engineer II – Senior EngineerTeam: Click Prediction, Bing Ads, MicrosoftLocation: BeijingMicrosoft AI & Research is seeking an experienced software development engineer to design and develop advanced enterprise focused AI product and solution to improve the customer's engagement by reducing the support cost, and improve customer's satisfaction. We are looking for a passionate, creative, analytical and experienced individual who love information retrieval, information extraction, machine learning, artificial intelligence, and shipping fast at massive scale.As a Senior Engineer you will design and build knowledge extraction algorithms from both Web and enterprise data, machine learning algorithms for text processing, question answering algorithms, data ingestion and serving systems, and applications to enable the advanced enterprise search experience. The person must have a strong R&D background in machine learning, Web scale knowledge extraction and natural language processing. Experience in areas like deep learning, spoken language systems, web search technology, and personalized Web services is also a plus.Basic Qualifications: 6 years of professional software development, with at least 3 years in big data or machine learning.Preferred Qualifications: 1.

Digital Marketing and Machine Learning Smart Insights


The launch of Google's new machine learning tool, RankBrain which contributes to search engine results, left many people wondering what impact machine learning would have in the realm of Search Engine Optimization (SEO). While RankBrain has been the first to really make its mark in this space, companies of all kinds are starting to put a greater focus on data gathering and storing, making machine learning more relevant. This allows you to automate and personalize certain marketing processes by letting your machine learning tools make decisions on content, call-to-actions, and even design, in real-time. Experts believe that machine learning will continue to grow across the mobile market space, acquiring an even larger presence within applications, digital assistants, and AI as a whole.