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 Information Retrieval


Bias already exists in search engine results, and it's only going to get worse

#artificialintelligence

The internet might seem like a level playing field, but it isn't. Safiya Umoja Noble came face to face with that fact one day when she used Google's search engine to look for subjects her nieces might find interesting. She entered the term "black girls" and came back with pages dominated by pornography. Noble, a USC Annenberg communications professor, was horrified but not surprised. For years she has been arguing that the values of the web reflect its builders--mostly white, Western men--and do not represent minorities and women.


Building a Content-Based Search Engine I: Quantifying Similarity - deep ideas

#artificialintelligence

The explosion of user-generated content on the internet during the last decades has left the world of querying multimedia data with unprecedented challenges. There is a demand for this data to be processed and indexed in order to make it available for different types of queries, whilst ensuring acceptable response times. An arguably important task is the retrieval of multimedia objects (e.g. We define two multimedia objects to be visually similar if they depict contents that "look similar" to humans. So far, this task has gained comparatively little research recognition.


The Low Hanging SEO Fruit You're Missing Out On

#artificialintelligence

This article covers several different methods to help you identify and seize opportunities to promote your site quickly and efficiently. I believe that, when it comes down to it, website promotion works best when based on the Pareto principle โ€“ that is, 20% of the pages create 80% of the traffic. This article will help you identify, optimize, and promote your best pages, the 20% that generate most of your traffic. As you probably know already, more and more business owners understand the importance of their website's ranking in Google's search results. As it is the go-to search engine for almost everyone and everything, Google has become the effective reality of the business world.



Google launched its own job search engine โ€“ here's how it works

The Independent - Tech

Google launched its own job search engine -- here's how it works The tech giant recently launched its own job search feature, Google for Jobs. As Business Insider's Matt Weinberger reports, the new feature employs machine learning-trained algorithms to sort and organise job listings from a range of employment sites including LinkedIn, Monster and Glassdoor. So if you decide to find your next gig on Google, you'll have a streamlined place to search and AI technology on your side. Here's 13 tips on how to get started using Google for Jobs: Follow Business Insider UK on Twitter. The Independent's bitcoin group on Facebook is the best place to follow the latest discussions and developments in cryptocurrency.


Artificial Intelligence and the Future of Search Engines

#artificialintelligence

It was not long ago that Artificial Intelligence (AI) was only in the realm of science fiction. Today, it has become a reality and is only growing more prominent in many different industries every day. This includes the internet as AI in search engine technology has been around for a few years. The algorithms used to rank pages have been affected considerably by AI already and that trend will continue into the foreseeable future. Currently, Google's RankBrain, an AI process used help set search engine rankings, is having a major impact which is only expected to expand.


The Search Problem in Mixture Models

arXiv.org Machine Learning

We consider the task of learning the parameters of a {\em single} component of a mixture model, for the case when we are given {\em side information} about that component, we call this the "search problem" in mixture models. We would like to solve this with computational and sample complexity lower than solving the overall original problem, where one learns parameters of all components. Our main contributions are the development of a simple but general model for the notion of side information, and a corresponding simple matrix-based algorithm for solving the search problem in this general setting. We then specialize this model and algorithm to four common scenarios: Gaussian mixture models, LDA topic models, subspace clustering, and mixed linear regression. For each one of these we show that if (and only if) the side information is informative, we obtain parameter estimates with greater accuracy, and also improved computation complexity than existing moment based mixture model algorithms (e.g. tensor methods). We also illustrate several natural ways one can obtain such side information, for specific problem instances. Our experiments on real data sets (NY Times, Yelp, BSDS500) further demonstrate the practicality of our algorithms showing significant improvement in runtime and accuracy.


How Search Engines Use Machine Learning: 9 Things We Know for Sure

#artificialintelligence

When we first started hearing about machine learning in the early 2010s, it seemed scary at first. Machine learning is essentially using algorithms to calculate trends, value, or other characteristics of specific things based on historical data. Google has even declared itself a machine learning-first company. If you want to learn more about the tactical side of this technology, Eric Enge has a great write-up on Moz explaining how machine learning impacts SEO from a mathematical standpoint. Search engines like to always experiment with how they can use this evolving technology, but here are nine ways we know that they are currently using machine learning and how it relates to SEO or digital marketing.


Sequence 2 Sequence Keyword Extraction (Neural Network) - Part 3

#artificialintelligence

We are finally going to get the code ready for our sequence 2 sequence neural network which is taking a machine learning approach to keyword extraction. This was part of a larger natural language processing project I did last year.


How to develop an integrated Paid Search and SEO strategy for e-commerce Smart Insights

#artificialintelligence

When it comes to digital marketing, pay per click (PPC) advertising and search engine optimisation (SEO) are arguably two sides of the same coin. However, all too often companies will focus on one at the expense of the other. At ClickThrough Marketing we provide an integrated digital marketing approach. Working with large-scale e-commerce sites, we have learnt the importance of combining PPC and SEO activities to gain greater client and market insight as well as streamline our own internal activities. Here, we look at four ways in which PPC and SEO can work together to deliver better results across the board.