In the past few weeks, we published (or received acceptance notices for) a number of papers related to Mr. DLib, research-paper recommender systems, and recommendations-as-a-service. Many of them were written during our time at the NII or in collaboration with the NII. Read more…
On 28th February, we released version 1.1.1 of Mr. DLib’s recommender system with some minor improvements and bug fixes: Improved 404 error handling for unknown document IDs Fix: The order of authors in the XML was not sorted properly Several Read more…
Stefan Feyer from the University of Konstanz had joined the Mr. DLib team for a six months internship. Yesterday, it was time to say goodbye to Stefan and we had a small farewell party at the National Institute of Informatics Read more…
Six months ago, we launched Mr. DLib’s recommendations-as-a-service for Academia. Time, to look back and provide some numbers: Since September 2016, Mr. DLib´s recommender system has delivered 60,836,800 recommendations to our partner Sowiport, and Sowiport’s users have clicked 91,545 of Read more…
We are proud to announce version 1.1 of Mr. DLib’s Recommender-System as-a-Service. The major new features are: A JavaScript Client to request recommendations from Mr. DLib. The JavaScript offers many advantages compared to a server-side processing of our recommendations. Among others, the main Read more…
Currently, all of Docear’s online services are down, including the recommender system. This means, you cannot register, log-in to download backups, or receive recommendations. As we have no time right now for the development of Docear, we are afraid that Read more…
Our paper titled “Stereotype and Most-Popular Recommendations in the Digital Library Sowiport” is accepted for publication at the 15th International Symposium on Information Science (ISI) in Berlin. Abstract: Stereotype and most-popular recommendations are widely neglected in the research-paper recommender-system and digital-library Read more…
This semester my colleague and I are teaching the Machine-Learning module CS7CS4 at Trinity College Dublin. We decided to publish the lecture slides on Slideshare. The slides contain 11 lectures about machine learning, covering aspects such as an introduction to machine Read more…
Two of our papers about weighting citations and terms in the context of user modeling and recommender systems got accepted at the iConference 2017. Here are the abstracts, and links to the pre-print versions: Evaluating the CC-IDF citation-weighting scheme: How effectively Read more…
A demonstration paper about the integration of Mr. DLib in JabRef is accepted for publication at ECIR 2017. We will update this post soon with more information and a pre-print.
Content-based filtering recommendations suffer from the problem that no human quality assessments are taken into account. This means a poorly written paper ppoor would be considered equally relevant for a given input paper pinput as high-quality paper pquality if pquality and ppoor contain the same Read more…
We are glad to announce that JabRef – one of the most popular open-source reference manager – will soon be using Mr. DLib´s recommender system to provide article recommendations to its users. The team of Mr. DLib and JabRef had several Skype calls, Read more…
Our servers for Mr. DLib’s recommender-system as-a-service (RaaS) are now monitored by UptimeRobot, a free monitoring service. You can access all our RaaS server statuses at this URL https://stats.uptimerobot.com/WLL5PUjN6 and you will see a dashboard like this: A click on one Read more…
We have integrated several new recommendation algorithms into Mr. DLib. Some recommendation algorithms are only ought as baselines for our researchers, others hopefully will further increase the effectiveness of Mr. DLib. Overall, Mr. DLib now uses the following recommendation algorithms in Read more…
So far, Mr. DLib’s recommender system was running only on a single server. Consequently, when me messed up something in the development environment, sometimes the production system was affected, i.e. down. From today on, we have two additional dedicated servers running, meaning Read more…
Update on 2018-03-15: We Are Hiring 1 Software Engineer & 1 Software Architect / Product Owner for a Recommender-System Business Start-up Updated on 2017-08-14: Here at Docear and Mr. DLib we have many exciting projects in the field of Read more…
We are proud to announce that the social science portal Sowiport is using Mr. DLib´s recommender-system as-a-service as first pilot partner. Sowiport pools and links quality information from domestic and international providers, making it available in one place. Sowiport currently Read more…
Update 2016-01-12: The salary in Tokyo would be around 1.600 US$ per month, not 1.400. 2015 has been a rather quiet year for Docear, but 2016 will be different. We have lots of ideas for new projects, and even better – Read more…
After releasing the Beta some weeks ago, we made some minor adjustments, and consider the current version 1.2 as stable. There are two major improvements and two bad news: Various improvements in the PDF Metadata retrieval function for Google Scholar. If you had Read more…
Docear 1.2 Beta is now available and has two major improvements: A new add-on to import any kind of highlighted text from PDFs This new add-on is a true milestone in the Docear development. Until now, you could only import Read more…
One reason why we originally started the development of Docear was our interest in how people are creating mind-maps and how the information contained in mind-maps could be used for building recommender systems and other user-modeling applications. As a result, we developed Docear’s Read more…
More than half a year ago, we started a call for donation to pay a freelancer who wanted to develop an add-on for LibreOffice and OpenOffice, comparable to Docear4Word. Originally, we estimated that it would take about 2 months before the work was completed, or at least a decent demo version was ready to released. Well, that estimate wasn’t quite precise – the developer hasn’t finished even an alpha version yet. In addition, we are still missing a significant amount of donations to fully pay the developer ($1,000 are missing).
The question arises, how to proceed? We see the following options:
1. Just wait
The freelancer is still working on the add-on. So, most likely he will finish the add-on some day – maybe in 2 months, maybe in 6 months, maybe in a year. However, I have to point out that my satisfaction with the current progress and outcomes are not overwhelming. Personally, I have some doubts that the final add-on will meet the quality expectations I have, and that probably most Docear users have. However, I suggest you get an idea of the add-on yourself. The freelancer sent me a demo version that you can try out. To do so, download the add-on, store it on your hard drive, and open the downloaded file with LibreOffice or OpenOffice. This should open an installation dialog, and you need to confirm all messages in the dialog. After the installation, you should restart Libre/OpenOffice. If you are using OpenOffice, you will have a Docear entry in the menu and in the tool bar (see screenshot below). If you are using LibreOffice, you will only have an entry in the menu.
In the past few weeks, several users reported that Docear could not retrieve metadata more from Google Scholar any more. It took as a while, but now we found and fixed the problem – hopefully. We need your help to Read more…
Our paper “The Architecture and Datasets of Docear’s Research Paper Recommender System” was accepted at the 3rd International Workshop on Mining Scientific Publications (WOSP 2014), which is held in conjunction with the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2014). Read more…
Compared to several other reference managers, Docear lacks a feature to directly import references from the Web. For instance, if you visit the detail page of a research article on a publisher’s website, you might wish to directly import the bibliographic data of that article to Docear. Many publishers offer export options for reference managers such as Endnote, RefWorks, or Zotero. So, how do you do it with Docear?
Fortunately, Docear uses the BibTeX format to store references. BibTeX is a de-facto standard for references that is supported by almost any publisher and any reference manager. So, read on to learn how to import bibliographic data from web-pages in two steps!