|
|
@conference{araqueTASS2015,
|
|
|
author = "Oscar Araque and Ignacio Corcuera-Platas and Constantino Rom{\'a}n-G{\'o}mez and Carlos A. Iglesias and J. Fernando S{\'a}nchez-Rada",
|
|
|
abstract = "This article presents the participation of the Intelligent Systems Group
|
|
|
(GSI) at Universidad Polit´ecnica de Madrid (UPM) in the Sentiment Analysis workshop
|
|
|
focused in Spanish tweets, TASS2015. This year two challenges have been
|
|
|
proposed, which we have addressed with the design and development of a modular
|
|
|
system that is adaptable to different contexts. This system employs Natural
|
|
|
Language Processing (NLP) and machine-learning technologies, relying also in previously
|
|
|
developed technologies in our research group. In particular, we have used a
|
|
|
wide number of features and polarity lexicons for sentiment detection. With regards
|
|
|
to aspect detection, we have relied on a graph-based algorithm. Once the challenge
|
|
|
has come to an end, the experimental results are promising.",
|
|
|
booktitle = "Proceedings of TASS 2015: Workshop on Sentiment Analysis at SEPLN co-located with 31st SEPLN Conference",
|
|
|
keywords = "Machine Learning, Natural Language Processing, Sentiment analysis, Aspect detection",
|
|
|
month = "September",
|
|
|
pages = "29-34",
|
|
|
title = "{A}spect based {S}entiment {A}nalysis of {S}panish {T}weets",
|
|
|
url = "http://ceur-ws.org/Vol-1397/gsi.pdf",
|
|
|
volume = "1397",
|
|
|
year = "2015",
|
|
|
}
|
|
|
|
|
|
|
|
|
@conference{220151,
|
|
|
author = "J. Fernando S{\'a}nchez-Rada and Carlos A. Iglesias and Ronald Gil",
|
|
|
address = "Beijing, China",
|
|
|
keywords = "sanchezrada;iglesias",
|
|
|
month = "July",
|
|
|
pages = "11--19",
|
|
|
title = "{A} {L}inked {D}ata {M}odel for {M}ultimodal {S}entiment and {E}motion {A}nalysis",
|
|
|
url = "http://aclweb.org/anthology/W/W15/W15-4202.pdf",
|
|
|
year = "2015",
|
|
|
}
|
|
|
|
|
|
|
|
|
@conference{220151,
|
|
|
author = "J. Fernando S{\'a}nchez-Rada and Carlos A. Iglesias and Ronald Gil",
|
|
|
address = "Beijing, China",
|
|
|
keywords = "sanchezrada;iglesias",
|
|
|
month = "July",
|
|
|
pages = "11--19",
|
|
|
title = "{A} {L}inked {D}ata {M}odel for {M}ultimodal {S}entiment and {E}motion {A}nalysis",
|
|
|
url = "http://aclweb.org/anthology/W/W15/W15-4202.pdf",
|
|
|
year = "2015",
|
|
|
}
|
|
|
|
|
|
|
|
|
@conference{araqueTASS2015,
|
|
|
author = "Oscar Araque and Ignacio Corcuera-Platas and Constantino Rom{\'a}n-G{\'o}mez and Carlos A. Iglesias and J. Fernando S{\'a}nchez-Rada",
|
|
|
abstract = "This article presents the participation of the Intelligent Systems Group
|
|
|
(GSI) at Universidad Polit´ecnica de Madrid (UPM) in the Sentiment Analysis workshop
|
|
|
focused in Spanish tweets, TASS2015. This year two challenges have been
|
|
|
proposed, which we have addressed with the design and development of a modular
|
|
|
system that is adaptable to different contexts. This system employs Natural
|
|
|
Language Processing (NLP) and machine-learning technologies, relying also in previously
|
|
|
developed technologies in our research group. In particular, we have used a
|
|
|
wide number of features and polarity lexicons for sentiment detection. With regards
|
|
|
to aspect detection, we have relied on a graph-based algorithm. Once the challenge
|
|
|
has come to an end, the experimental results are promising.",
|
|
|
booktitle = "Proceedings of TASS 2015: Workshop on Sentiment Analysis at SEPLN co-located with 31st SEPLN Conference",
|
|
|
keywords = "Machine Learning, Natural Language Processing, Sentiment analysis, Aspect detection",
|
|
|
month = "September",
|
|
|
pages = "29-34",
|
|
|
title = "{A}spect based {S}entiment {A}nalysis of {S}panish {T}weets",
|
|
|
url = "http://ceur-ws.org/Vol-1397/gsi.pdf",
|
|
|
volume = "1397",
|
|
|
year = "2015",
|
|
|
}
|
|
|
|
|
|
@article{onyx15,
|
|
|
author = "J. Fernando S{\'a}nchez-Rada and Carlos A. Iglesias",
|
|
|
abstract = "Extracting opinions and emotions from text is becoming more and more important, especially since the advent of micro-blogging and social networking.
|
|
|
Opinion mining has become particularly popular and now gathers many public services, datasets and lexical resources.
|
|
|
Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications.
|
|
|
Some of the barriers for developing such resources are the diversity of emotion theories and the absence of a common vocabulary to express emotion.
|
|
|
This article presents a semantic vocabulary, called Onyx, intended to provide support to represent emotions in lexical resources and emotion analysis services.
|
|
|
It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with lemon, an increasingly popular RDF model for representing lexical entries.
|
|
|
This approach also means a new and interesting way to work with different theories of emotion.
|
|
|
As part of our work, Onyx has been aligned with EmotionML and WordNet-Affect.
|
|
|
",
|
|
|
awards = "JCR 1.265 2014 Q2",
|
|
|
comments = "JCR 1.265 2014 Q2",
|
|
|
issn = "0306-4573",
|
|
|
journal = "Information Processing {\&}amp; Management",
|
|
|
keywords = "onyx;emotion analysis;linked data",
|
|
|
month = "January",
|
|
|
pages = "99-114",
|
|
|
title = "{O}nyx: {A} {L}inked {D}ata {A}pproach to {E}motion {R}epresentation",
|
|
|
url = "http://www.sciencedirect.com/science/article/pii/S030645731500045X",
|
|
|
volume = "52",
|
|
|
year = "2016",
|
|
|
}
|
|
|
|
|
|
|
|
|
@incollection{CarlosIglesias16,
|
|
|
author = "Carlos A. Iglesias and J. Fernando S{\'a}nchez-Rada and Gabriela Vulcu and Paul Buitelaar",
|
|
|
booktitle = "Sentiment Analysis in Social Networks",
|
|
|
chapter = "Linked Dat",
|
|
|
isbn = "9780128044124",
|
|
|
keywords = "sentiment analysis;social networks",
|
|
|
month = "October",
|
|
|
pages = "46-66",
|
|
|
publisher = "Morgan Kauffman",
|
|
|
title = "{L}inked {D}ata {M}odels for {S}entiment and {E}motion {A}nalysis in {S}ocial {N}etworks",
|
|
|
url = "http://store.elsevier.com/Sentiment-Analysis-in-Social-Networks/Federico-Alberto-Pozzi/isbn-9780128044124/",
|
|
|
year = "2016",
|
|
|
}
|
|
|
|
|
|
|
|
|
@conference{Sánchez-Rada2016,
|
|
|
author = "J. Fernando S{\'a}nchez-Rada and Carlos A. Iglesias",
|
|
|
booktitle = "Proceedings DSAA 2016 Special Track on Emotion and Sentiment in Intelligent Systems and Big Social Data Analysis (SentISData).",
|
|
|
month = "October",
|
|
|
title = "{S}enpy: {A} {P}ragmatic {L}inked {S}entiment {A}nalysis {F}ramework",
|
|
|
year = "2016",
|
|
|
}
|
|
|
|
|
|
@conference{maia14,
|
|
|
author = "S{\'a}nchez-Rada, J. Fernando and Iglesias, Carlos A. and Coronado, Miguel",
|
|
|
abstract = "Online services are no longer isolated. The release of public APIs and technologies such as web hooks are allowing users and developers to access their information easily. Intelligent agents could use this information to provide a better user experience across services, connecting services with smart automatic behaviours or actions. However, agent platforms are not prepared to easily add external sources such as web services, which hinders the usage of agents in the so-called Evented or Live Web. As a solution, this paper introduces an event-based architecture for agent systems, in accordance with the new tendencies in web programming. In particular, it is focused on personal agents that interact with several web services. With this architecture, called MAIA, connecting to new web services does not involve any modification in the platform.",
|
|
|
address = "Warsaw, Poland",
|
|
|
booktitle = "Proceedings of 2014 IEEE/WIC/ACM International Conference on Intelligent Agent Technology",
|
|
|
keywords = "event, agent architecture, web hook",
|
|
|
month = "August",
|
|
|
organization = "IAT",
|
|
|
publisher = "IEEE Computer Society Press",
|
|
|
title = "{MAIA}: {A}n {E}vent-based {M}odular {A}rchitecture for {I}ntelligent {A}gents",
|
|
|
year = "2014",
|
|
|
}
|
|
|
|
|
|
@conference{eurosentiment-demo,
|
|
|
author = "S{\'a}nchez-Rada, J. Fernando and Gabriela Vulcu and Iglesias, Carlos A. and Paul Buitelaar",
|
|
|
abstract = "Sentiment and Emotion Analysis strongly depend on quality language resources, especially sentiment dictionaries. These resources are usually scattered, heterogeneous and limited to specific domains of application by simple algorithms. The EUROSENTIMENT project addresses these issues by 1) developing a common language resource representation model for sentiment analysis, and APIs for sentiment analysis services based on established Linked Data formats (lemon, Marl, NIF and ONYX) 2) by creating a Language Resource Pool (a.k.a. LRP) that makes available to the community existing scattered language resources and services for sentiment analysis in an interoperable way. In this paper we describe the available language resources and services in the LRP and some sample applications that can be developed on top of the EUROSENTIMENT LRP.",
|
|
|
booktitle = "ISWC 2014 Posters {\&} Demonstrations Track",
|
|
|
editor = "Matthew Horridge, Marco Rospocher, Jacco van Ossenbruggen",
|
|
|
keywords = "eurosentiment",
|
|
|
pages = "145-148",
|
|
|
title = "{EUROSENTIMENT}: {L}inked {D}ata {S}entiment {A}nalysis",
|
|
|
url = "http://ceur-ws.org/Vol-1272/paper_116.pdf",
|
|
|
volume = "1272",
|
|
|
year = "2014",
|
|
|
}
|
|
|
|
|
|
@conference{es3lod14,
|
|
|
author = "Gabriela Vulcu and Paul Buitelaar and Sapna Negi and Bianca Pereira and Mihael Arcan and Barry Coughlan and S{\'a}nchez-Rada, J. Fernando and Iglesias, Carlos A.",
|
|
|
abstract = "We present a methodology for legacy language resource adaptation that generates domain-specific
|
|
|
sentiment lexicons organized around domain entities described with lexical information and
|
|
|
sentiment words described in the context of these entities. We explain the steps of the methodology
|
|
|
and we give a working example of our initial results. The resulting lexicons are modelled as Linked
|
|
|
Data resources by use of established formats for Linguistic Linked Data (lemon, NIF) and for linked
|
|
|
sentiment expressions (Marl), thereby contributing and linking to existing Language Resources in
|
|
|
the Linguistic Linked Open Data cloud.
|
|
|
",
|
|
|
address = "Reykjavik, Iceland",
|
|
|
booktitle = "th International Workshop on EMOTION, SOCIAL SIGNALS, SENTIMENT {\&} LINKED OPEN DATA, co-located with LREC 2014,",
|
|
|
keywords = "domain lexion, sentiment analysis",
|
|
|
month = "May",
|
|
|
organization = "LREC2014",
|
|
|
title = "{G}enerating {L}inked-{D}ata based {D}omain-{S}pecific {S}entiment {L}exicons from {L}egacy {L}anguage and {S}emantic {R}esources",
|
|
|
year = "2014",
|
|
|
}
|
|
|
|
|
|
@mastersthesis{clave,
|
|
|
author = "S{\'a}nchez-Rada, J. Fernando",
|
|
|
abstract = "This project aims to introduce an event-based architecture for intelligent agents, inaccordance with the new tendencies in the Evented Web.The reason for this change is that agent communication is no longer suitable for theinmense amount of data generated nowadays and its nature. At least, not for their usein evolving scenarios where data sources interact without previous con guration. This isexactly what the precursors of the Live Web envision, and it is beginning to show in the newgeneration of evented applications, which enable customized interactions and a high level ofcommunication between dierent services.The proposed architecture shown in this document, called Maia, is based on a centralpiece or event router, which controls the ow of information/events to and from the connectedentities. These entities can be either event-aware agents or simply data sources andsubscribers. Thus giving a higher exibility than current technologies and easing the developmentof advanced systems by not requiring the complexity associated with agent systemsin all of the nodes.To demonstrate the feasibility and capabilities of the Maia architecture, a prototype hasbeen implemented which is also explained in detail in this document. It is based on the eventdrivenI/O server side JavaScript environment Node.js for the event routing components,and adapted Jason BDI agent platform as an example of a subscribed multi-agent system.Using this prototype, the bene ts of using Maia are illustrated by developing a personalagent capable of booking train tickets and that combines access to services, linked data andcommon sense reasoning.",
|
|
|
keywords = "agents, web hooks",
|
|
|
school = "ETSIT-UPM",
|
|
|
title = "{D}esign and {I}mplementation of an {A}gent {A}rchitecture {B}ased on {W}eb {H}ooks",
|
|
|
year = "2012",
|
|
|
}
|
|
|
|
|
|
@conference{ftt14,
|
|
|
author = "S{\'a}nchez-Rada, J. Fernando and Torres, Marcos and Iglesias, Carlos A. and Roberto Maestre and Raquel Peinado",
|
|
|
abstract = "Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked data approach for modelling sentiment and emotions about financial entities. We aim at integrating sentiment information from different communities for providers, and complements existing initiatives such as FIBO. The approach has been validated in the semantic annotation of tweets of several stocks in the Spanish stock market, including its sentiment information.",
|
|
|
booktitle = "Second International Workshop on Finance and Economics on the Semantic Web (FEOSW 2014)",
|
|
|
keywords = "linked data, semantic, finance, sentiment analysis, emotions",
|
|
|
title = "{A} {L}inked {D}ata {A}pproach to {S}entiment and {E}motion {A}nalysis of {T}witter in the {F}inancial {D}omain",
|
|
|
url = "http://nadir.uc3m.es/feosw2014/proceedings.html",
|
|
|
year = "2014",
|
|
|
}
|
|
|
|
|
|
@conference{onyx2013,
|
|
|
author = "S{\'a}nchez-Rada, J. Fernando and Iglesias, Carlos A.",
|
|
|
abstract = "There are several different standardised and widespread formats to represent emotions. However, there is no standard semantic model yet. This paper presents a new ontology, called Onyx, that aims to become such a standard while adding concepts from the latest Semantic Web models. In particular, the ontology focuses on the representation of Emotion Analysis results. But the model is abstract and inherits from previous standards and formats. It can thus be used as a reference representation of emotions in any future application or ontology. To prove this, we have translated resources from EmotionML representation to Onyx.
|
|
|
We also present several ways in which developers could benefit from using this ontology instead of an ad-hoc presentation. Our ultimate goal is to foster the use of semantic technologies for emotion Analysis while following the Linked Data ideals.",
|
|
|
address = "Torino, Italy",
|
|
|
booktitle = "Proceedings of the First International Workshop on Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI (ESSEM 2013)",
|
|
|
month = "December",
|
|
|
organization = "AI*IA, Italian Association for Artificial Intelligence",
|
|
|
pages = "71-82",
|
|
|
publisher = "CEUR-WS",
|
|
|
title = "{O}nyx: {D}escribing {E}motions on the {W}eb of {D}ata",
|
|
|
volume = "1096",
|
|
|
year = "2013",
|
|
|
}
|
|
|
|
|
|
@conference{ldl2013,
|
|
|
author = "Paul Buitelaar and Mihael Arcan and Iglesias, Carlos A. and S{\'a}nchez-Rada, J. Fernando and Carlo Strapparava",
|
|
|
abstract = "In this paper we describe the specification of a
|
|
|
model for the semantically interoperable represen-
|
|
|
tation of language resources for sentiment analysis. The model integrates ‘lemon’, an RDF-based model for the specification of ontology-lexica
|
|
|
(Buitelaar et al. 2009), which is used increasingly for the representation of language resources as Linked Data, with 'Marl', an RDF-based model for the representation of sentiment annotations (Westerski et al., 2011; S{\'a}nchez-Rada et al., 2013).",
|
|
|
address = "Pisa, Italy",
|
|
|
booktitle = " 2nd Workshop on Linked Data in Linguistics (LDL-2013): Representing and linking lexicons, terminologies and other language data. Collocated with the Conference on Generative Approaches to the Lexicon",
|
|
|
editor = "Christian Chiarcos, Philipp Cimiano, Thierry Declerck, John P. McCrae",
|
|
|
keywords = "sentim",
|
|
|
month = "September",
|
|
|
pages = "1-8",
|
|
|
publisher = "Association for Computational Linguistics",
|
|
|
title = "{L}inguistic {L}inked {D}ata for {S}entiment {A}nalysis",
|
|
|
year = "2013",
|
|
|
}
|
|
|
|
|
|
@conference{ATS14,
|
|
|
author = "Jordi Atserias and Marieke van Erp and Isa Maks and Germ{\'a}n Rigau and S{\'a}nchez-Rada, J. Fernando",
|
|
|
address = "Reykjavik, Iceland",
|
|
|
booktitle = "Proceedings of Come Hack with OpeNER!” workshop at the 9th Language Resources and Evaluation Conference (LREC’14)",
|
|
|
pages = "5",
|
|
|
publisher = "European Language Resources Association (ELRA)",
|
|
|
title = "{E}uro{L}ove{M}ap: {C}onfronting feelings from {N}ews",
|
|
|
year = "2014",
|
|
|
}
|
|
|
|