Seattle-based Institute Allen, founded by Microsoft founder Pual Allen, is looking to build a new, meaning-based search engine. It is also known as the AL2 abbreviation. The institute is offering a new service for free called Semantic Search Engine.
And why is it looking to build a new search engine, and what are the problems with current search engines like google scholar and PubMed?
When researchers search for information in the search engine, they are faced with the problem of the amount of information and articles produced annually by search engines. One researcher suggests that the larger the amount of information available, the easier it is to examine the most important.
The semantic search engine wants to make it easier to find relevant information. The new search engine is an attempt to provide useful information from the content of articles in an efficient way. It’s not about finding content from a title, it’s about putting a general concept of content into the title.
“No one can resist the advancement of science and technology,” says Dr. Etzioni. Which article is most relevant to the topic? Which article has the highest quality? Has anyone else worked on this or related issues? By using these search engines, researchers can answer these questions in seconds, thus solving problems faster and getting things done faster. “
Nicola Jones in the weekly science journal Nature / News acknowledged that Semantic Scholar searches for articles in computer science. The group is working to extend its scope of work to one year.
The AI2 team has begun work on computer science-related articles to familiarize them with the results of the work. Subsequently, the team decided to extend the results of their work to other sciences as well. Medical science is a top priority. Etizoni says in the journal above: I’m talking to people who say that doctors in emergencies are looking for solutions in Google Scholar and on their mobile phones.
Some of the features, but not the great features of this project, are quickly cited by the researchers and the number of times the articles are cited.
The research team explains how this search engine helps to do the research: it searches the web and finds all available pdf files that are subject to computer science and all graphs, texts And lists them for the next step. The system identifies priority articles, reducing the length of the list, and sorting them according to the type of article and how effective the article may be. This search engine also helps ordinary people to research related topics.
Users can increase their filters using other options. However, researchers want to help people access topics quickly.