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Keenious is an AI-based tool that allows you to search for similar or related articles based on either an article or written text. The AI analyses the downloaded article, a link to the article, a selected passage from the article or a written text and recommends similar or related content. Keenious runs in either a web browser or Word application and is licensed to the University of Helsinki until the end of year 2027.
Keenious currently supports text analysis exclusively in English. However, it allows for cross-language searches in nearly 100 different languages. This is facilitated by Microsoft Azure's translation program, which converts the text into English prior to analysis. Note that while there is no length restriction for texts in English, non-English texts are limited to a maximum of 20,000 characters. Users are permitted up to 10 cross-language searches per day.
If you want the tool to recommend articles in the same language as the analyzed article, click the "cross language" button (the top right corner) off.
Keenious application works for all disciplines.
Its data comes from OpenAlex, which contains a very large amount (~hundreds of millions) of metadata (but not full texts) of both open and non-open access journal articles.Book articles will be included later on. OpenAlex includes material predominantly in English.
Keenious Webinar given by the developers in April 2023. Length 1.10h, subtitled.
Keenious is hosting introductory webinars for the Keenious Research Recommendation tool twice a month.
These are introductory sessions, so no experience with Keenious is required!
Registration, dates etc.:
https://keenious.notion.site/webinar?v=8e465dc66bbc4bbdbfcc5555c0e8b54a&pvs=4
Keenious is a very versatile tool for mapping research. Unlike most common information retrieval methods, it is not based on inventing keywords, but on analysing the text you already know or the text you write yourself and based on this analysis by AI. Thus, Keenious is useful at least for the following purposes:
Questions about Keenious? Need technical support? Would your faculty or department like a presentation on Keenious?
Please, contact: kirjasto@helsinki.fi
Has Keenious been useful to you? Is there anything you would like to improve? Do you have any thoughts on the different ways of using it?
Tell us! All feedback is helpful. The address is kirjasto@helsinki.fi