Tag Archives: California

GSoC 2017 – Recap and Results

We are very pleased to announce that all of this year’s Google Summer of Code students made it successful through the program and passed their projects. All codes have been submitted, merged and are ready to be examined by the rest of the world.

Marco Fossati, Dimitris Kontokostas, Tommaso Soru, Domenico Potena, Emanuele Storti , anastasia Dimiou, Wouter Maroy, Peng Xu, Sandro Coelho and Ricardo Usbeck, members of the DBpedia Community, did a great job in mentoring 7 students from around the world. All of the students enjoyed the experiences made during the program and will hopefully continue to contribute to DBpedia in the future.

“GSoC is the perfect opportunity to learn from experts, get to know new communities, design principles and work flows.” (Ram G Athreya)”

Now, we would like to take that opportunity to  give you a little recap of the projects mentored by DBpedia members during the past months. Just click below for more details .

 

DBpedia Mappings Front-End Administration by Ismael Rodriguez

The goal of the project was to create a front-end application that provides a user-friendly interface so the DBPedia community can easily view, create and administrate DBpedia mapping rules using RML. The developed system includes user administration features, help posts, Github mappings synchronization, and rich RML related features such as syntax highlighting, RML code generation from templates, RML validation, extraction and statistics. Part of these features are possible thanks to the interaction with the DBPedia Extraction Framework. In the end, all the functionalities and goals that were required have been developed, with many functional tests and the approval of the DBpedia community. The system is ready for production deployment. For further information, please visit the project blog.  Mentors: Anastasia Dimou and Wouter Maroy (Ghent University), Dimitris Kontokostas (GeoPhy HQ).

Chatbot for DBpedia by Ram G Athreya

DBpedia Chatbot is a conversational chatbot for DBpedia which is accessible through the following platforms: a Web Interface, Slack and Facebook Messenger.

The bot is capable of responding to users in the form of simple short text messages or through more elaborate interactive messages. Users can communicate or respond to the bot through text and also through interactions (such as clicking on buttons/links). The bot tries to answer text based questions of the following types: natural language questions, location information, service checks, language chapters, templates and banter. For more information, please follow the link to the project site. Mentor: Ricardo Usbeck (AKSW).

Knowledge Base Embeddings for DBpedia by Nausheen Fatma

Knowledge base embeddings has been an active area of research. In recent years a lot of research work such as TransE, TransR, RESCAL, SSP, etc. has been done to get knowledge base embeddings. However none of these approaches have used DBpedia to validate their approach. In this project, I want to achieve the following tasks: i) Run the existing techniques for KB embeddings for standard datasets. ii) Create an equivalent standard dataset from DBpedia for evaluations. iii) Evaluate across domains. iv) Compare and Analyse the performance and consistency of various approaches for DBpedia dataset along with other standard datasets. v) Report any challenges that may come across implementing the approaches for DBpedia. For more information, please follow the links to her project blog and GitHub-repository. Mentors: Tommaso Soru (AKSW) and  Sandro Coelho (KILT).

Knowledge Base Embeddings for DBpedia by Akshay Jagatap

The project defined embeddings to represent classes, instances and properties by implementing Random Vector Accumulators with additional features in order to better encode the semantic information held by the Wikipedia corpus and DBpedia graphs. To test the quality of embeddings generated by the RVA, lexical memory vectors of locations were generated and tested on a modified subset of the Google Analogies Test Set. Check out further information via Akshay’s GitHub-repo. Mentors: Tommaso Soru (AKSW) and Xu Peng (University of Alberta).

The Table Extractor by Luca Vergili

Wikipedia is full of data hidden in tables. The aim of this project was to explore the possibilities of exploiting all the data represented with the appearance of tables in Wiki pages, in order to populate the different chapters of DBpedia through new data of interest. The Table Extractor has to be the engine of this data “revolution”: it would achieve the final purpose of extracting the semi structured data from all those tables now scattered in most of the Wiki pages. In this page you can observe dataset (english and italian) extracted using table extractor . Furthermore you can read log file created in order to see all operations made up for creating RDF triples. I recommend to also see this page, that contains the idea behind the project and an example of result extracted from log files and .ttl dataset. For more details see Luca’s Git-Hub repository. Mentors: Domenico Potena and Emanuele Storti (Università Politecnica delle Marche).

 

Unsupervised Learning of DBpedia Taxonomy by Shashank Motepalli

Wikipedia represents a comprehensive cross-domain source of knowledge with millions of contributors. The DBpedia project tries to extract structured information from Wikipedia and transform it into RDF.

The main classification system of DBpedia depends on human curation, which causes it to lack coverage, resulting in a large amount of untyped resources. DBTax provides an unsupervised approach that automatically learns a taxonomy from the Wikipedia category system and extensively assigns types to DBpedia entities, through the combination of several NLP and interdisciplinary techniques. It provides a robust backbone for DBpedia knowledge and has the benefit of being easy to understand for end users. details about his work and his code can e found on the projects site. Mentors: Marco Fossati (Università degli Studi di Trento) and Dimitris Kontokostas (GeoPhy HQ). 

The  Wikipedia List-Extractor by Krishanu Konar

This project aimed to augment upon the already existing list-extractor project by Federica in GSoC 2016. The project focused on the extraction of relevant but hidden data which lies inside lists in Wikipedia pages. Wikipedia, being the world’s largest encyclopedia, has humongous amount of information present in form of text. While key facts and figures are encapsulated in the resource’s infobox, and some detailed statistics are present in the form of tables, but there’s also a lot of data present in form of lists which are quite unstructured and hence its difficult to form into a semantic relationship. The main objective of the project was to create a tool that can extract information from Wikipedia lists and form appropriate RDF triplets that can be inserted in the DBpedia dataset. Fore details on the code and about the project check Krishanu’s blog and GitHub-repository. Mentors: Marco Fossati (Università degli Studi di Trento), Domenico Potena and Emanuele Storti (Università Politecnica delle Marche). 

Read more

We are regularly growing our community through GSoC and can deliver more and more opportunities to you. Ideas and applications for the next edition of GSoC are very much welcome. Just contact us via email or check our website for details.

Again, DBpedia is planning to be a vital part of the GSoC Mentor Summit, from October 13th -15th, at the Google Campus in Sunnyvale California. This summit is a way to say thank you to the mentors for the great job they did during the program. Moreover it is a platform to discuss what can be done to improve GSoC and how to keep students involved in their communities post-GSoC.

And there is more good news to tell.  DBpedia wants to meet up with the US community during the 11th DBpedia Community Meeting in California.  We are currently working on the program and keep you posted as soon as registration is open.

So, stay tuned and check  Twitter, Facebook and the Website or subscribe to our Newsletter for latest news and updates.

See you soon!

Yours,

DBpedia Association

Retrospective: 2nd US DBpedia Community meeting in California

After the largest DBpedia meeting to date we decided it was time to cross the Atlantic for the second time for another meetup. Two weeks ago the 8th DBpedia Community Meeting was held in Sunnyvale, California on October 27th 2016.

Main Event

Pablo Mendes from Lattice Data Inc. opened the main event with a short introduction setting the tone for the evening. After that Dimitris Kontokostas gave technical and organizational DBpedia updates. The main event attracted attendees with lightning talks from major companies actively using DBpedia or interested in knowledge graphs in general.

Four major institutions described their efforts to organize reusable information in a centralized knowledge representation. Google’s Tatiana Libman presented (on behalf of Denny Vrandečić) the impressive scale of the Google Knowledge graph, with 1B+ entities and over 100 billion facts.

Tatiana Libman from Google
Tatiana Libman from Google

Yahoo’s Nicolas Torzec presented the Yahoo knowledge graph, with focus on their research on extracting data from Web tables to expand their knowledge which includes DBpedia as an important part. Qi He from LinkedIn focused mostly on how to model a knowledge graph of people and skills, which becomes particularly interesting with the possibility of integration with Microsoft’s Satori Graph. Such an integration would allow general domain knowledge and very specific knowledge about professionals complementing one another. Stas Malyshev from Wikidata presented statistics on their growth, points of contact with DBpedia as well as an impressive SPARQL query interface that can be used to query the structured data that they are generating.

Three other speakers focused on the impact of DBpedia in machine learning and natural language processing. Daniel Gruhl from IBM Watson gave the talk “Truth for the impatient” where he showed that a knowledge model built from DBpedia can help costs and time to value for extracting entity mentions with higher accuracy. Pablo Mendes from Lattice Data Inc. presented their approach that leverages DBpedia and other structured information sources for weak supervision to obtain very strong NLP extractors. Sujan Perera from IBM Watson discussed the problem of identifying implicit mentions of entities in tweets and how the knowledge represented in DBpedia can be used to help uncover those references.

Another three speakers focused on applications of DBpedia and knowledge graphs. Margaret Warren from Metadata Authoring Systems, LLC presented ImageSnippets and how background knowledge from DBpedia allows better multimedia search through inference. For instance, by searching for “birds” you may find pictures that haven’t been explicitly tagged as birds but for which the fact can be inferred from DBpedia. Jans Aasman from Franz Inc presented their company’s approach to Data Exploration with Visual SPARQL Queries. They described opportunities for graph analytics in the medical domain, and discussed how DBpedia has been useful in their applications. Finally, Wang-Chiew Tan presented their research at RIT relating to building chatbots, among other projects that relate to using background knowledge stored in computers to enrich real life experiences.

8th-dbpedia-meeting_california
Nicolas Torzec from Yahoo

Overall the talks were very high quality and fostered plenty of discussions afterwards. We finalized the event with a round of introductions where every attendee got to say their name and affiliation to help them connect with one another throughout the final hour of the event.

All slides and presentations are also available on our Website and you will find more feedback and photos about the event on Twitter via #DBpediaCA.

We would like to thank Yahoo for hosting the event, Google Summer of Code 2016 mentor summit as the reason we were in the area and collocated the DBpedia meeting, the Institute for Applied Informatics for supporting the DBpedia Association, ALIGNED – Software and Data Engineering for funding the development of DBpedia as a project use-case and last but not least OpenLink Software for continuous hosting the main DBpedia Endpoint.

Thanks to Pablo Mendes for providing oneliner summaries for the talks 🙂

So now, we are looking forward to the next DBpedia community meeting which will be held in Europe again. We will keep you informed via the DBpedia Website and Blog.

Your DBpedia Association

California is calling for the next DBpedia Community Meeting.

Less than 24 hours left to reserve your seat for our 2nd US DBpedia Community meeting. The meeting will be held in Sunnyvale on October 27th 2016, hosted by Yahoo. Over 85 participants registered so far, we will offer 20 more tickets. So come and get your ticket to be part of this event.

The event will feature talks from Yahoo, IBM Watson, LinkedIn, Lattice, Wikimedia, Frank Inc, Knoesis, RIT and ImageSnippets. The topics will include knowledge graphs & machine learning, open data, open source and startups. Please read below on different ways you can participate. We are looking forward to meeting again in person with the US-based DBpedia community.

Quick facts

Schedule

Please check our schedule for the next DBpedia Community Meeting here: http://wiki.dbpedia.org/meetings/California2016

Acknowledgments

If you would like to become a sponsor for the 8th DBpedia Meeting, please contact the DBpedia Association.

Yahoo! For hosting the meeting and the catering
Google Summer of Code 2016 Amazing program and the reason some of our core DBpedia devs are visiting California
ALIGNED – Software and Data Engineering For funding the development of DBpedia as a project use-case and covering part of the travel cost
Institute for Applied Informatics For supporting the DBpedia Association
OpenLink Software For continuous hosting of the main DBpedia Endpoint

Organisation

Registration

Attending the DBpedia Community meeting is free of charge, but seats are limited. Make sure to register to reserve a seat.

Location

The meeting will take place at the Yahoo headquarters in Sunnyvale.

Address: Yahoo! (Building E, 701 First Avenue, Sunnyvale, CA)

Many thanks to Yahoo & Nicolas Torzec for providing a bigger room and hosting the event!

Check our website for further updates and like us on Facebook.

Your DBpedia Association