semantics-aware graph-based recommender systems exploiting linked open data
TRANSCRIPT
Semantics-aware Graph-based Recommender Systems exploiting
Linked Open DataCataldo Musto, Pasquale Lops, Pierpaolo Basile,
Marco de Gemmis Giovanni Semeraro (Università degli Studi di Bari ‘Aldo Moro’, Italy - SWAP Research Group)
UMAP 2016 24th Conference on User Modeling,
Adaptation and Personalization Halifax (Canada)
July 15, 2016
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Linked Open Data
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data
Methodology to publish, share and link structured data on the Web
Definition
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open DataCornerstones
1.
2.Use of RDF to publish data on the Web
Re-Use of existing properties to express an agreed semantics and connect data sources
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)What is it?
A (large) set of interconnected semantic datasetsCataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)What kind of datasets?
Each bubble is a dataset!Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)How many data?
9960 datasets and 149 billions triplessource: http://stats.lod2.eu
today!
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)
DBpedia is the structured RDF mapping of Wikipedia
http://dbpedia.org
It is the core of the LOD cloud.
DBpedia
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)Example: unstructured content from Wikipedia
example (Wikipedia page)
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)How are these data represented?
The Matrix
Don Davis
http://dbpedia.org/resource/Category:Films_shot_in_Australia
Films shot in Australia
dcterms:subject
dbpedia-owl:musicComposer
http://dbpedia.org/resource/Don_Davis_(composer)
\
dcterms:subject
dcterms:subject
dbo:
runt
ime
dbpe
dia-
owl:d
irect
ordcterms:subject
dcterms:subject
Dystopian Films136American Action Thriller Films
Cyberpunk Films The Wachowskis
http://dbpedia.org/resource/The_Wachowskis
http://dbpedia.org/resource/Dystopian_FIlms
http://dbpedia.org/resource/Cyberpunk_Films
http://dbpedia.org/resource/American_Action_Thriller_FIlms
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
Several interesting (non-trivial) features come into play!Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Linked Open Data (cloud)How are these data represented?
The Matrix
Don Davis
http://dbpedia.org/resource/Category:Films_shot_in_Australia
Films shot in Australia
dcterms:subject
dbpedia-owl:musicComposer
http://dbpedia.org/resource/Don_Davis_(composer)
\
dcterms:subject
dcterms:subject
dbo:
runt
ime
dbpe
dia-
owl:d
irect
ordcterms:subject
dcterms:subject
Dystopian Films136American Action Thriller Films
Cyberpunk Films The Wachowskis
http://dbpedia.org/resource/The_Wachowskis
http://dbpedia.org/resource/Dystopian_FIlms
http://dbpedia.org/resource/Cyberpunk_Films
http://dbpedia.org/resource/American_Action_Thriller_FIlms
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
Several interesting (non-trivial) features come into play!Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Research Questions
(1) Can we use Linked Open Data for Recommender Systems?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Research Questions
(2) Is it possible to automatically select the most promising properties among those available in the LOD cloud?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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i4
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u2
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MethodologyGraph-based Data Model - original representation
Original Graph-based data model
Users and Items are connected according to users’ preferences
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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i4
u1
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u3
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MethodologyGraph-based Data Model - DBpedia Mapping
If we are able to map the items in the dataset with
the entities in the
LOD cloud, our representation can be extended with new data points
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
MethodologyGraph-based Data Model - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subject
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
Methodologyexample - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subject
Many new information can be injected in the
graph
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
Methodologyexample - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subject
How to get recommendations?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Graph-based Recommendation Algorithm
Insight: - Calculate PageRank score for each item node. - Sort PageRank scores in a descending order. - Select top-k recommendations
PageRank with Priors
. T. H. Haveliwala. Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search. IEEE Trans. Knowl. Data Eng., 15(4):784–796, 2003.
Reference
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
20
i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
Methodologyexample - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subject
Is it possibile to automatically select the most promising
properties?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
21
i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
Methodologyexample - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subject
XX
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
22
i4
u1
u2
u3
u4
dcterms:subject
http://dbpedia.org/resource/Films_About_Rebellions
Films about Rebellions
dbprop:director
Quentin Tarantino
dbprop:director
Methodologyexample - LOD-boosted representation
1999 films
http://dbpedia.org/resource/1999_films
dcterms:subject
dcterms:subjectXX
X
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experiments
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Research QuestionsDo graph-based recommender systems benefit of the introduction of LOD-based features?
Do graph-based recommender systems exploiting LOD benefit of the adoption of feature selection techniques?
1/2
1.
2.
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Research Questions3.
4.
2/2Is there any correlation between the choice of the FS technique and the behavior of the algorithm? (e.g., better diversity or better F1) ?
How does our methodology perform with respect to state-of-the-art algorithms?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experimental EvaluationDescription of the dataset
MovieLens 100k983 users1,682 movies100,000 ratings55.17% positive ratings84.43 ratings/user (avg.)48.48 ratings/item (avg.)93.7% sparsity
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experimental EvaluationDescription of the dataset
DBbook dataset6,181 users6,733 movies72,372 ratings45,85% positive ratings11.70 ratings/user (avg.)10.74 ratings/item (avg.)99.8% sparsity
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experimental EvaluationGraph Representations :: Recap
GBasic Graph with collaborative data points
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experimental Evaluation
GLOD Graph extended with all the properties gathered from the LOD cloud
Graph Representations :: Recap
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
30
Experimental Evaluation
GLOD+FS Graph encoding only the most relevant properties selected by a feature selection technique FS
Graph Representations :: Recap
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
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Experimental EvaluationExperimental Protocol
Algorithm PageRank with Priors
Data Split 5-fold Cross Validation for MovieLens Train/Test for DBbook
Graph Representation G, GLOD, GLOD+FS
Feature Selection Techniques PageRank, Chi-Square, Information Gain, Gain Ratio, mRMR, PCA, SVM
#Selected Features top-10, top-30, top-50 properties
Evaluation Metrics F1, Intra-List Diversity, Run Time
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 1
32
Impact of LOD-based features.
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
F1@5
F1@10
G
G_LOD
G
G_LOD
53 55 57 59 61
60,83
54,24
60,23
53,89
Experiment 1
33
Impact of LOD-based features :: F1-measure
Improvement only on MovieLens
F1@5
F1@10
G
G_LOD
G
G_LOD
53 56 59 62 65
64,21
55,04
64,31
55,02
MovieLens
DBbook
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Run Time (min.)
G
G_LOD
50 262,5 475 687,5 900
880
72
Experiment 1
34Tremendous increase in the run time
Impact of LOD-based features :: Run Time
Run Time (min.)
G
G_LOD
50 662,5 1275 1887,5 2500
2.433
100
MovieLens
DBbook
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 2
35
Impact of Feature Selection techniques
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 2
36GLOD (baseline) = 54,24
Impact of Feature Selection :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
53 53,5 54 54,5 5554,31
54,12
54,06
54,21
54,2
54,21
54,12
54,13
53,96
53,98
54,13
54,19
54,29
54,29
54,06
53,97
53,72
53,82
54,14
53,97
54,18
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
53 53,5 54 54,5 5554,31
54,12
54,06
54,21
54,2
54,21
54,12
54,13
53,96
53,98
54,13
54,19
54,29
54,29
54,06
53,97
53,72
53,82
54,14
53,97
54,18
Experiment 2
37
Tree out of seven techniques (and only with 50 features) overcome the baseline
Impact of Feature Selection :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
53 53,5 54 54,5 5554,31
54,12
54,06
54,21
54,2
54,21
54,12
54,13
53,96
53,98
54,13
54,19
54,29
54,29
54,06
53,97
53,72
53,82
54,14
53,97
54,18
Experiment 2
38Typically, the larger the number of features, the better the F1
#50
#50
#50
#50
#50
#30
#30
(best)
Impact of Feature Selection :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
63,5 63,825 64,15 64,475 64,864,286
64,19
64,25
64,26
64,19
64,19
64,18
64,32
64,27
64,31
64,3
64,2
64,27
64,22
64,33
64,45
64,35
64,34
64,23
64,35
64,31
Experiment 2
39
#10
#10
#10
#10
#10
#10
Impact of Feature Selection :: DBbook :: F1@10
#10
GLOD (baseline) = 64,20Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
63,5 63,825 64,15 64,475 64,864,286
64,19
64,25
64,26
64,19
64,19
64,18
64,32
64,27
64,31
64,3
64,2
64,27
64,22
64,33
64,45
64,35
64,34
64,23
64,35
64,31
Experiment 2
40
#10
#10
#10
#10
#10
#10
Impact of Feature Selection :: DBbook :: F1@10
#10
All the techniques overcome the baseline at least once
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
PageRank
mRMR
Chi-Square
SVM
Gain Ratio
Inf. Gain
PCA
103050103050103050103050103050103050103050
63,5 63,825 64,15 64,475 64,864,286
64,19
64,25
64,26
64,19
64,19
64,18
64,32
64,27
64,31
64,3
64,2
64,27
64,22
64,33
64,45
64,35
64,34
64,23
64,35
64,31
Experiment 2
41On DBbook best results are obtained with 10 features!
#10
#10
#10
#10
#10
#10
(best)
Impact of Feature Selection :: DBbook :: F1@10
#10
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Run Time (min.) - MovieLens
GLOD
GLOD+PCA
50 262,5 475 687,5 900
581
880
Experiment 2
42Significant decrease
Impact of Feature Selection techniques :: Run Time
Run Time (min.) - DBbook
GLOD
GLOD+IG
50 687,5 1325 1962,5 2600
1.341
2433
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
43
Trade-off between F1 and diversity
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
44
Trade-off between F1 and diversity
Can the choice of the feature selection technique endogenously induce an higher diversity (or,
respectively, an higher F1) of the recommendations?
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
45
Trade-off between F1 and diversity :: MovieLens :: F1@5
G_LOD = Baseline
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
46
PCA maximizes F1, at the expense of a little diversity
Trade-off between F1 and diversity :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
47
Gain Ratio and SVM sacrifice F1, to induce an higher diversity
Trade-off between F1 and diversity :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
48
PageRank obtains a good compromise between F1 and Diversity
Trade-off between F1 and diversity :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 3
49
Similar outcomes on DBbook…but more techniques have a good impact
Trade-off between F1 and diversity :: MovieLens :: F1@5
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 4
50
Comparison to State of the artBPRMF (Bayesian Personalized Ranking) [+]
U2U-KNN (User to User CF) I2I-KNN (Item to Item CF)
POPULAR (Popularity-based baseline)
[+] S. Rendle, C.Freudenthaler, Z. Gantner, L. Schmidt-Thieme: BPR: Bayesian Personalized Ranking from Implicit Feedback. UAI 2009.
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 4
51
Comparison to State of the Art :: MovieLens
50
54
58
62
66
F1@5 F1@10
60,88
54,31
59,16
51,4
59,16
51,78
59,7
52,2
58,35
50,22
I2I-KNN U2U-KNN BPRMF POPULAR PR (G_LOD+PCA)
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 4
52
50
54
58
62
66
F1@5 F1@10
60,88
54,31
59,16
51,4
59,16
51,78
59,7
52,2
58,35
50,22
I2I-KNN U2U-KNN BPRMF POPULAR PR (G_LOD+PCA)
PageRank with Priors boosted with LOD is the best-performing approach
Comparison to State of the Art :: MovieLens
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 4
53
50
54
58
62
66
F1@5 F1@10
60,88
54,31
59,16
51,4
59,16
51,78
59,7
52,2
58,35
50,22
I2I-KNN U2U-KNN BPRMF POPULAR PR (G_LOD+PCA)
Even state-of-the-art approaches based on Matrix Factorization are overcame by our methodology
Comparison to State of the Art :: MovieLens
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Experiment 4
54
50
55
60
65
70
F1@5 F1@10
64,45
55,4
62,72
52,96
62,63
52,9
62,29
51,93
62,1
51,11
I2I-KNN U2U-KNN BPRMF POPULAR PR (G_LOD+PCA)
Behavior confirmed on DBbook
Comparison to State of the Art :: DBbook
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Conclusions
55Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Recap
56
Methodolology1. PageRank with Priors as base algorithm2. Mapping of the items with nodes in the Linked
Open Data Cloud 3. Expansion of the data points and injection of new
nodes and edges 4. Use of feature selection to automatically select the
most promising properties
INVESTIGATION ABOUT THE EFFECTIVENESS OF LINKED OPEN DATA INGRAPH-BASED RECOMMENDER SYSTEMS
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
Lessons Learned
57
Evaluation1. PageRank with Priors benefit of the injection of data points
coming from the LOD cloud2. Feature Selection techniques improve the results but need
to be properly tuned, since its usage is not always useful 3. A significant connection between the choice of the feature
selection technique and the maximization of a specific evaluation metric exists
4. PageRank with Priors boosted with LOD significantly overcomes state-of-the-art approaches
INVESTIGATION ABOUT THE EFFECTIVENESS OF LINKED OPEN DATA INGRAPH-BASED RECOMMENDER SYSTEMS
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016
thank youCataldo Musto
[email protected] @cataldomusto
http://www.di.uniba.it/~swap
Cataldo Musto, Pasquale Lops, Pierpaolo Basile, Marco de Gemmis, Giovanni Semeraro Semantics-aware Graph-based Recommender Systems Exploiting Linked Open Data. UMAP 2016, Halifax (Canada). 15.07.2016