Showing posts with label SAC2016. Show all posts
Showing posts with label SAC2016. Show all posts

ACM SAC 2016 Travel Report

From the 4th to the 8th of April I had the pleasure to participate the 31st ACM Symposium on Applied Computing (ACM SAC), which was held in beautiful city Pisa, Italy. I was there to present my full paper "Measuring Semantic Distance for Linked Open Data-enabled Recommender Systems" and to participate the Student Research Competition sponsored by Microsoft.

This year, there were over 500+ registrations from 59 countries at this conference. There were 37 tracks and the overall acceptance rate for this year is 24%.

Keynotes:

There were two keynotes given by John Mylopoulos and Marco Conti, respectively. The first keynote is about the requirements problem in Software Engineering and the second keynote is about "From MANET to people-centric computing and communications.


Semantic Web Track:

There were two sessions with eight papers for Semantic Web Track where three of the participants two of the participants from our institute. Pasquale Minervini presented "Leveraging the Schema in Latent Factor Models for Knowledge Graph Completion" and another college Feng Gao presented "QoS-Aware Adaptation for Complex Event Service" in another (SOA) track.


Social Network and Media Analysis Track (SONAMA):

One of the papers in this track I'm interested in was "Inferring Semantic Interest Profiles from Twitter Followees: Does Twitter Know Better than Your Friends?" from Christoph Besel, University of Passau, Germany, which is related to my work. Although many previous works focused on using tweets for inferring user interest profiles, they used the alternative source (followees) to retrieve user interest profiles, which are based on the tendency that more and more users are consuming feeds instead of producing content on the social networks.

Student Research Competition (SRC):

I also participated in SAC SRC and went through 2nd round (top-5 list) and it was a good opportunity to compete across different disciplines. Congrats to all top-3 winners! 

Lunch

Banquet

What would make the conference better?

It would be better to have a Twitter channel to communicate and disseminate activities during the conference. Next year, it will be in Morocco and hope I could attend again:).

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Update after the conference:

The proceedings are available from June, 2016

RESIM (REsource SIMilarity) for Linked Data

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DESCRIPTION

The resim.jar file is an implementation of RESIM (REsource SIMilarity) measure. The measure is designed to calculate the semantic similarity between two resources in a Knowlege Graph (e.g., DBpedia, zhishi.me) with a SPARQL Endpoint. RESIM is presented in [1] and then it is improved in [2] and the summary of the measure is presented in [3]. The implementation extends the measure further by enabling different properties for two resources, e.g., for incoming indirect link between dbpedia:Steve_Jobs and dbpedia:Apple_Inc., it can be connected by dbpedia:Steve_Jobs<-dbpedia-owl:keyPerson<-dbpedia:NexT->dbpedia-owl:successor->dbpedia:Apple_Inc. while in the paper we restrict the property should be the same.
When writing a paper or producing a software application, tool, or interface based on the library, please kindly cite the source [2].

REQUIREMENT

  • Java 1.7
  • JENA 2.11.2

EXAMPLE 1

public static void main(String[] args) {

    // similarity measure settings
    List<String> additionalPropertyList = Arrays.asList(
            "<http://purl.org/dc/terms/subject>", 
            "<http://www.w3.org/2000/01/rdf-schema#subClassOf>", 
            "<http://www.w3.org/2004/02/skos/core#narrowerOf>", 
            "<http://www.w3.org/2004/02/skos/core#broaderOf>",
            "<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>"
            );
    List<String> includePropertyList = Arrays.asList(
            "<http://purl.org/dc/terms/subject>", 
            "<http://www.w3.org/2000/01/rdf-schema#subClassOf>", 
            "<http://www.w3.org/2004/02/skos/core#narrower>", 
            "<http://www.w3.org/2004/02/skos/core#broader>",
            "<http://www.w3.org/1999/02/22-rdf-syntax-ns#type>"
            );
    List<String> excludePropertyList = Arrays.asList(
            "<http://dbpedia.org/ontology/wikiPageWikiLink>" 
            );

    // initialize similarity measure
    // param1: SPARQL Endpoint URL
    // param2: pattern for property - default: "http://dbpedia.org/ontology/
    // param3: include property list
    // param4: additional property list to pattern
    // param5: exclude property list
    ResourceSimilarityMeasure rsm = new ResourceSimilarityMeasure("http://dbpedia.org/sparql", null, null, additionalPropertyList, excludePropertyList);    

    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Drink>", "<http://dbpedia.org/resource/Mouth>", 2));

}

EXAMPLE 2

public static void main(String[] args) {

    List<String> excludePropertyList = Arrays.asList("<http://dbpedia.org/ontology/wikiPageWikiLink>");
    ResourceSimilarityMeasure rsm = new ResourceSimilarityMeasure("http://dbpedia.org/sparql", null, null, null, excludePropertyList);  

    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Apple_Inc.>", "<http://dbpedia.org/resource/Steve_Jobs>", 2));
    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Apple_Inc.>", "<http://dbpedia.org/resource/Steve_Wozniak>", 2));
    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Apple_Inc.>", "<http://dbpedia.org/resource/Jonathan_Ive>", 2));
    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Apple_Inc.>", "<http://dbpedia.org/resource/Microsoft>", 2));
    System.out.println(rsm.getSimilarity("<http://dbpedia.org/resource/Apple_Inc.>", "<http://dbpedia.org/resource/IPad>", 2));

    // Printed results
    0.7107697604926099
    0.26084710667467736
    0.13425729687979637
    0.6239711506085717
    0.7341358492281069
    Started: 18.1.2016 21:54:42 Finished: 18.1.2016 21:55:12

}
  • The ResourceSimilarityMeasure requires 5 parameters. The first one is a SPARQL Endpoint (e.g., DBpedia SPARQL Endpoint) and the other ones are used for controling the property list for this measure.
  • The 2nd parameter (pattern) is used with 4th, 5th parameters. For example, the default pattern of property for this measure is "http://dbpedia.org/ontology/" (i.e., DBpedia Ontology properties) and it will consider/exclude the list of properties if there is an additional property list or an exclude property list exist.
  • The 3rd parameter is an include property list that controls property list for this measure in a strict way. That is, the measure will only consider this property list if you define the list.

REFENRECES

  1. Computing the Semantic Similarity of Resources in DBpedia for Recommendation Purposes, Guangyuan Piao, Safina showkat Ara, John G. Breslin 5th Joint International Semantic Technology Conference, Yichang, China, 2015
  2. Measuring Semantic Similarity for Linked Open Data-enabled Recommender Systems, Guangyuan Piao and John G. Breslin, The 31st ACM/SIGAPP Symposium on Applied Computing, Pisa, Italy, 2016
  3. Exploiting the Semantic Similarity of Interests in a Semantic Interest Graph for Social Recommendations, Guangyuan Piao, The 31st ACM/SIGAPP Symposium on Applied Computing, Pisa, Italy, 2016

Review of 2015

Research

The year 2015 is finished and I've been in Ireland and Insight for 1 year and 6 months. Doing research here gives me quite different experience than previous research experience, and it poses good opportunities as well as challenges for myself.

Independent:  

You have to grow up and be able to do your research (not projects) with your ideas and opinions, and conduct experiments by your own. I remembered the seminar I participated at the beginning of the PhD journey and the speaker described our academic supervisor as advisor since it is more appropriate. That means our advisor is who giving advices for your research but not who telling you every step you should move forward, and usually our supervisors also too busy to do so. 

At first, I could not start own research and conduct experiment by myself, and there was always uncertainty about myself and I realized the way I've been trained always was "supervised" by others. It reminds me the time in South Korea when I was a master student as well as an employee in a company where I received a lot of things to-do every day from senior members. In contrast, I did not receive any call here, and all communication has been done through emails which is still a surprising fact for me. Thanks to God, even I have a lot of improvements to achieve, I have started the research, with advice from my supervisor.

I started to recognize the statements from (So you want to do a PhD from Open University) that a PhD is confirming your "research independence", i.e., you have to demonstrate that:

  1. Ability to do research by yourself, rather than simply doing what your supervisor tells you
  2. Awareness of where your work fits in relation to the discipline, and what it contributes to the discipline
  3. Mature overview of the discipline




Insight Centre: 


There have been many changes for Insight@Galway which was formally well known as DERI. Our former director Prof. Steffan Decker moved to Germany and we have new director Prof. Dietrich Rebholz-Schuhmann. Interestingly, many researchers, including PhD students, Postdocs moved to Germany as well. There are many career paths for graduates from here including academic positions as well as industry ones, or even some of them start running own startups etc.


Conference

After several attempts for conferences, I've published two full papers in JIST2015 and SAC2016, and I found that it is really important to publish or try to publish your results in any conference or journal to get started, and get feedbacks from the experts. In my previous experience, I've been recommended do not to read and present a conference paper for a seminar during previous studies. However, here, one thing I love is that top conferences have the same importance to top journals. There is an interesting article to read if you have the same wondering: https://homes.cs.washington.edu/~mernst/advice/conferences-vs-journals.html
At the end of the year, I submitted a paper to ESWC2016 which has very interested tutorials for me http://2016.eswc-conferences.org/program/workshops-tutorials and hope I will have an opportunity to attend it:). Another conference I'd like to participate is UMAP2016 which is also highly related to my research. So... Fingers crossed for the upcoming new year.