Collaborating Authors

Information Retrieval

Using Computer Programs and Search Problems for Teaching Theory of Computation

Communications of the ACM

The theory of computation is one of the crown jewels of the computer science curriculum. It stretches from the discovery of mathematical problems, such as the halting problem, that cannot be solved by computers, to the most celebrated open problem in computer science today: the P vs. NP question. Since the founding of our discipline by Church and Turing in the 1930s, the theory of computation has addressed some of the most fundamental questions about computers: What does it mean to compute the solution to a problem? Which problems can be solved by computers? Which problems can be solved efficiently, in theory and in practice?

Archaeological search engine adds a new dimension to 'digging'


Apps that can precisely identify shards, coins or heel bones: archaeology has embraced artificial intelligence. Alex Brandsen is working on a search engine that scans vast quantities of text from an archaeological viewpoint. An archaeologist by training, he spent time working as a programmer, before returning to University to study for a PhD combining the two "I've noticed at [archaeology] conferences over the last two years that AI has become a real buzzword, and a lot of money and energy are going into it." Brandsen is working on a search engine for archaeologists that can quickly and effectively scan all the excavation reports of Dutch finds. "For example, if you search under burial rites in the Middle Ages, the search engine needs to understand that the term 1200 CE is also relevant. There are thousands of terms that mean Middle Ages and it has to find them all. It must also be able to distinguish between a bill as a bladed weapon and a researcher whose name is Bill."

Useful sites for finding datasets for Data Analysis tasks


Let's now look at some of the useful sites for finding open and publicly available datasets, quickly and without much hassle. Google Dataset Search is a search engine dedicated to finding datasets. It is a search engine over metadata from data providers. This implies that it indexes over the descriptions of a dataset instead of its content. So if a dataset is available publicly, there is a good chance, that it will pop up in the Google dataset search.

Elastic Transformers


Contextual bit -- as we have seen, keyword search can be (sometimes) limiting. Context is definitely highly beneficial to receive results that are semantically related to what you are looking for: when looking for "virus threat", "virus risks" also appear, etc

Archie, the very first search engine, was released 30 years ago today


On Archie's 30th anniversary, we salute the world's first search engine, a pioneer that paved the way for giants to come. Archie was first released to the general public on Sept. 10, 1990. It was developed as a school project by Alan Emtage at McGill University in Montreal. According to an interview with Digital Archaeology, Emtage had been working as a grad student in 1989 in the university's information technology department. His job required him to find software for other students and faculty.

Emergent Web Intelligence: Advanced Information Retrieval - Programmer Books


Emergent Web Intelligence: Advanced Information Retrieval PDF Download for free: Book Description: This volume reviews cutting-edge technologies and insights related to XML-based and multimedia information access and data retrieval. And by applying new techniques to real-world scenarios, it details how organizations can gain competitive advantages.

The search engine boss who wants to help us all plant trees

BBC News

This week we speak to Christian Kroll, the founder and chief executive of internet search engine Ecosia. Christian Kroll wants nothing less than to change the world. "I want to make the world a greener, better place," he says. "I also want to prove that there is a more ethical alternative to the kind of greedy capitalism that is coming close to destroying the planet." The 35-year-old German is the boss of search engine Ecosia, which has an unusual but very environmentally friendly business model - it gives away most of its profits to enable trees to be planted around the world. Founded by Christian in 2009, Ecosia makes its money in the same way as Google - from advertising revenues.

Learn how to reach the first page of Google with this SEO training bundle


TL;DR: Learn how to drive more traffic to your website with the SEO Blueprint for Ranking on Google bundle for $29.99, a 94% savings as of Aug. 28. Digital marketing trends come and go, but there's one thing that never changes: You won't be as relevant if you're not on the first page of Google search, and there's data to back it up. Reports show that 75% of people never bother to scroll past the first page of search results, so regardless of how stellar your content is, barely anyone will see it unless you know what you're doing. We're talking about search engine optimization (SEO), which is a set of processes that help your site and content skyrocket to the first page and gain relevance. It takes time, energy, and patience to get your SEO in a good place, but the SEO Blueprint Course Bundle can certainly help.

Mozilla and Google renew Firefox search agreement


Mozilla and Google have extended their arrangement to keep Google the default search engine within the Firefox browser until at least 2023, ZDNet reported. The companies have not formally announced the deal, which ZDNet estimates is worth between $400 and $450 million per year, but are expected to announce it later this fall. The current arrangement was due to expire at the end of 2020. "Mozilla's search partnership with Google is ongoing, with Google as the default search provider in the Firefox browser in many places around the world, Mozilla spokesperson Justin O'Kelly said in an email to The Verge. "We've recently extended the partnership, and the relationship isn't changing."

Amazon Comprehend adds five new languages to Custom Entity Recognition


Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to analyze text documents and identify insights such as sentiment, entities, and topics from text. You can use Custom Entity Recognition to identify terms that are specific to your domain. For example, you can instantly extract product names, financial entities or any term relevant to you from unstructured text documents. Starting today, Amazon Comprehend is adding support for the following five new languages to Custom Entity Recognition: French, German, Italian, Portuguese, and Spanish.