Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2014
Connecting words with senses, namely, sight, hearing, taste, smell and touch, to comprehend the s... more Connecting words with senses, namely, sight, hearing, taste, smell and touch, to comprehend the sensorial information in language is a straightforward task for humans by using commonsense knowledge. With this in mind, a lexicon associating words with senses would be crucial for the computational tasks aiming at interpretation of language. However, to the best of our knowledge, there is no systematic attempt in the literature to build such a resource. In this paper, we present a sensorial lexicon that associates English words with senses. To obtain this resource, we apply a computational method based on bootstrapping and corpus statistics. The quality of the resulting lexicon is evaluated with a gold standard created via crowdsourcing. The results show that a simple classifier relying on the lexicon outperforms two baselines on a sensory classification task, both at word and sentence level, and confirm the soundness of the proposed approach for the construction of the lexicon and the usefulness of the resource for computational applications.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
In this paper, we experiment with a resource consisting of metaphorically annotated proverbs on t... more In this paper, we experiment with a resource consisting of metaphorically annotated proverbs on the task of word-level metaphor recognition. We observe that existing feature sets do not perform well on this data. We design a novel set of features to better capture the peculiar nature of proverbs and we demonstrate that these new features are significantly more effective on the metaphorically dense proverb data.
Artistic creation is often based on the concept of blending. Linguistic creativity is no exceptio... more Artistic creation is often based on the concept of blending. Linguistic creativity is no exception, as demonstrated for instance by the importance of metaphors in poetry. Blending can also be used to evoke a secondary concept while playing with an already given piece of language, either with the intention of making the secondary concept well perceivable to the reader, or instead, to subtly evoke something additional. Current language technology can do a lot in this connection, and automated language creativity can be useful in cases where input or target are to change continuously, making human production not feasible. In this work we present a system that takes existing well-known expressions and innovates them by bringing in a novel concept coming from evolving news. The technology is composed of several steps concerned with the selection of the sortable concepts and the production of novel expressions, largely relying on state of the art corpus-based methods. Proposed application...
Proceedings of the Third Workshop on Metaphor in NLP, 2015
Language is the main communication device to represent the environment and share a common underst... more Language is the main communication device to represent the environment and share a common understanding of the world that we perceive through our sensory organs. Therefore, each language might contain a great amount of sensorial elements to express the perceptions both in literal and figurative usage. To tackle the semantics of figurative language, several conceptual properties such as concreteness or imegeability are utilized. However, there is no attempt in the literature to analyze and benefit from the sensorial elements for figurative language processing. In this paper, we investigate the impact of sensorial features on metaphor identification. We utilize an existing lexicon associating English words to sensorial modalities and propose a novel technique to automatically discover these associations from a dependency-parsed corpus. In our experiments, we measure the contribution of the sensorial features to the metaphor identification task with respect to a state of the art model. The results demonstrate that sensorial features yield better performance and show good generalization properties.
While humans are capable of building connections between words and sensorial modalities by using ... more While humans are capable of building connections between words and sensorial modalities by using commonsense knowledge, it is not straightforward for machines to interpret sensorial information. To this end, a lexicon associating words with human senses, namely sight, hearing, taste, smell and touch, would be crucial. Nonetheless, to the best of our knowledge, there is no systematic attempt in the literature to build such a resource. In this paper, we propose a computational method based on bootstrapping and corpus statistics to automatically associate English words with senses. To evaluate the quality of the resulting lexicon, we create a gold standard via crowdsourcing and show that a simple classifier relying on the lexicon outperforms two baselines on a sensory classification task, both at word and sentence level. The results confirm the soundness of the proposed approach for the construction of the lexicon and the usefulness of the resource for computational applications.
In this paper, we combine existing NLP techniques with minimal supervision to build memory tips a... more In this paper, we combine existing NLP techniques with minimal supervision to build memory tips according to the keyword method, a well established mnemonic device for second language learning. We present what we believe to be the first extrinsic evaluation of a creative sentence generator on a vocabulary learning task. The results demonstrate that NLP techniques can effectively support the development of resources for second language learning.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2013
We present BRAINSUP, an extensible framework for the generation of creative sentences in which us... more We present BRAINSUP, an extensible framework for the generation of creative sentences in which users are able to force several words to appear in the sentences and to control the generation pro- cess across several semantic dimensions, namely emotions, colors, domain relatedness and phonetic properties. We evaluate its performance on a creative sentence generation task, showing its capability of generating well-formed, catchy and effective sentences that have all the good qualities of slogans produced by human copywriters.
Proceeding IUI '13 Companion Proceedings of the companion publication of the 2013 international conference on Intelligent user interfaces companion Pages 55-56 , 2013
In this paper, we introduce a system that supports the naming process by exploiting natural langu... more In this paper, we introduce a system that supports the naming process by exploiting natural language processing and linguistic creativity techniques in a completely unsupervised fashion. The system generates two types of neologisms based on the category of the service to be named and the properties to be underlined. While the first type consists of homophonic puns and metaphors, the second consists of neologisms that are produced by adding Latin suffixes to English words or homophonic puns. During this process, both semantic appropriateness and sound pleasantness of the generated names are taken into account.
Computational Linguistics and Intelligent Text …, 2013
In this paper, we propose a computational approach to automate the generation of neologisms by ad... more In this paper, we propose a computational approach to automate the generation of neologisms by adding Latin suffixes to English words or homophonic puns. This approach takes into account both semantic appropriateness and sound pleasantness of words. Our analysis of the generated neologisms provides interesting clues for understanding which technologies can successfully be exploited for the task, and the results of the evaluation show that the system that we developed can be a useful tool for supporting the generation of creative names.
Computational Linguistics and Intelligent Text …, 2013
In this paper, we systematically analyze the effect of incorporating different levels of syntacti... more In this paper, we systematically analyze the effect of incorporating different levels of syntactic and semantic information on the accuracy of emotion recognition from text. We carry out the evaluation in a supervised learning framework, and employ tree kernel functions as an intuitive and effective way to generate different feature spaces based on structured representations of the input data. We compare three different formalisms to encode syntactic information enriched with semantic features. These features are obtained from hand-annotated resources as well as distributional models. For the experiments, we use three datasets annotated according to the same set of emotions. Our analysis indicates that shallow syntactic information can positively interact with semantic features. In addition, we show how the three datasets can hardly be combined to learn more robust models, due to inherent differences in the linguistic properties of the texts or in the annotation.
Like its predecessors in 1996 (University of Twente, the Netherlands) and 2002 (ITC-irst, Trento,... more Like its predecessors in 1996 (University of Twente, the Netherlands) and 2002 (ITC-irst, Trento, Italy), this Third International Workshop on Computational Humor (IWCH 2012) focusses on the possibility to find algorithms that allow understanding and generation of humor. There is the general aim of modeling humor, and if we can do that, it will provide us with lots of information about our cognitive abilities in general, such as reasoning, remembering, understanding situations, and understanding conversational partners. But it also provides us with information about being creative, making associations, storytelling and language use. Many more subtleties in face-to-face and multiparty interaction can be added, such as using humor to persuade and dominate, to soften or avoid a face threatening act, to ease a tense situation or to establish a friendly or romantic relationship. One issue to consider is: when is a humorous act appropriate?
Proceedings of the 50th Annual Meeting of the …, 2012
In this paper, we propose a computational approach to generate neologisms consisting of homophoni... more In this paper, we propose a computational approach to generate neologisms consisting of homophonic puns and metaphors based on the category of the service to be named and the properties to be underlined. We describe all the linguistic resources and natural language processing techniques that we have exploited for this task. Then, we analyze the performance of the system that we have developed. The empirical results show that our approach is generally effective and it constitutes a solid starting point for the automation of the naming process.
Abstract The name of a company or a brand is the key element to a successful business. A good nam... more Abstract The name of a company or a brand is the key element to a successful business. A good name is able to state the area of competition and communicate the promise given to customers by evoking semantic associations. Although various resources provide distinct tips for inventing creative names, little research was carried out to investigate the linguistic aspects behind the naming mechanism. Besides, there might be latent methods that copywriters unconsciously use.
Abstract In todaypsilas world, many systems and approaches make it possible for us to be guided b... more Abstract In todaypsilas world, many systems and approaches make it possible for us to be guided by the recommendations they provide. Personalization, which intends to resolve the problems caused by the huge amount of information around, is the main goal to be achieved by these systems. In this paper, we represent the Web based recommendation system that we have developed by using personalization techniques combining machine learning with automated reasoning.
Colors have a very important role on our perception of the world. We often associate colors with ... more Colors have a very important role on our perception of the world. We often associate colors with various concepts at different levels of consciousnes and these associations can be relevant to many fields such as education and advertisement. However, to the best of our knowledge, there are no systematic approaches to aid the automatic development of resources encoding this kind of knowledge. In this paper, we propose three computational methods based on image analysis, language models, and latent semantic analysis to automatically associate colors to words. We compare these methods against a gold standard obtained via crowdsourcing. The results show that each method is effective in capturing different aspects of word-color associations.
Vocabulary acquisition is a very important step for learning a new language. On the other hand, m... more Vocabulary acquisition is a very important step for learning a new language. On the other hand, many learners find this step difficult and time consuming. Several vocabulary teaching methods try to facilitate this step with various verbal and visual tips. However, the preparation of these tips generally necessitates a huge amount of time, money and human labor. In this paper, we propose to exploit Natural Lanugage Processing driven creativity to develop an automatic system for task of vocabulary teaching. This system can automatically generate memorization tips for the words which users would like to memorize. The preliminary results are promising and motivating for further investigation, since they show that our approach can be quite effective on the related task.
This paper aims to shed some light on the concept of virality - especially in social networks - a... more This paper aims to shed some light on the concept of virality - especially in social networks - and to provide new insights on its structure. We argue that: (a) virality is a phe- nomenon strictly connected to the nature of the content being spread, rather than to the influencers who spread it (b) virality is a phenomenon with many facets, i.e. under this generic term several different effects of persuasive communication are comprised and they only partially overlap. To give ground to our claims, we provide initial experiments in a machine learning framework to show how various aspects of virality can be independently predicted according to content features.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2014
Connecting words with senses, namely, sight, hearing, taste, smell and touch, to comprehend the s... more Connecting words with senses, namely, sight, hearing, taste, smell and touch, to comprehend the sensorial information in language is a straightforward task for humans by using commonsense knowledge. With this in mind, a lexicon associating words with senses would be crucial for the computational tasks aiming at interpretation of language. However, to the best of our knowledge, there is no systematic attempt in the literature to build such a resource. In this paper, we present a sensorial lexicon that associates English words with senses. To obtain this resource, we apply a computational method based on bootstrapping and corpus statistics. The quality of the resulting lexicon is evaluated with a gold standard created via crowdsourcing. The results show that a simple classifier relying on the lexicon outperforms two baselines on a sensory classification task, both at word and sentence level, and confirm the soundness of the proposed approach for the construction of the lexicon and the usefulness of the resource for computational applications.
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016
In this paper, we experiment with a resource consisting of metaphorically annotated proverbs on t... more In this paper, we experiment with a resource consisting of metaphorically annotated proverbs on the task of word-level metaphor recognition. We observe that existing feature sets do not perform well on this data. We design a novel set of features to better capture the peculiar nature of proverbs and we demonstrate that these new features are significantly more effective on the metaphorically dense proverb data.
Artistic creation is often based on the concept of blending. Linguistic creativity is no exceptio... more Artistic creation is often based on the concept of blending. Linguistic creativity is no exception, as demonstrated for instance by the importance of metaphors in poetry. Blending can also be used to evoke a secondary concept while playing with an already given piece of language, either with the intention of making the secondary concept well perceivable to the reader, or instead, to subtly evoke something additional. Current language technology can do a lot in this connection, and automated language creativity can be useful in cases where input or target are to change continuously, making human production not feasible. In this work we present a system that takes existing well-known expressions and innovates them by bringing in a novel concept coming from evolving news. The technology is composed of several steps concerned with the selection of the sortable concepts and the production of novel expressions, largely relying on state of the art corpus-based methods. Proposed application...
Proceedings of the Third Workshop on Metaphor in NLP, 2015
Language is the main communication device to represent the environment and share a common underst... more Language is the main communication device to represent the environment and share a common understanding of the world that we perceive through our sensory organs. Therefore, each language might contain a great amount of sensorial elements to express the perceptions both in literal and figurative usage. To tackle the semantics of figurative language, several conceptual properties such as concreteness or imegeability are utilized. However, there is no attempt in the literature to analyze and benefit from the sensorial elements for figurative language processing. In this paper, we investigate the impact of sensorial features on metaphor identification. We utilize an existing lexicon associating English words to sensorial modalities and propose a novel technique to automatically discover these associations from a dependency-parsed corpus. In our experiments, we measure the contribution of the sensorial features to the metaphor identification task with respect to a state of the art model. The results demonstrate that sensorial features yield better performance and show good generalization properties.
While humans are capable of building connections between words and sensorial modalities by using ... more While humans are capable of building connections between words and sensorial modalities by using commonsense knowledge, it is not straightforward for machines to interpret sensorial information. To this end, a lexicon associating words with human senses, namely sight, hearing, taste, smell and touch, would be crucial. Nonetheless, to the best of our knowledge, there is no systematic attempt in the literature to build such a resource. In this paper, we propose a computational method based on bootstrapping and corpus statistics to automatically associate English words with senses. To evaluate the quality of the resulting lexicon, we create a gold standard via crowdsourcing and show that a simple classifier relying on the lexicon outperforms two baselines on a sensory classification task, both at word and sentence level. The results confirm the soundness of the proposed approach for the construction of the lexicon and the usefulness of the resource for computational applications.
In this paper, we combine existing NLP techniques with minimal supervision to build memory tips a... more In this paper, we combine existing NLP techniques with minimal supervision to build memory tips according to the keyword method, a well established mnemonic device for second language learning. We present what we believe to be the first extrinsic evaluation of a creative sentence generator on a vocabulary learning task. The results demonstrate that NLP techniques can effectively support the development of resources for second language learning.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2013
We present BRAINSUP, an extensible framework for the generation of creative sentences in which us... more We present BRAINSUP, an extensible framework for the generation of creative sentences in which users are able to force several words to appear in the sentences and to control the generation pro- cess across several semantic dimensions, namely emotions, colors, domain relatedness and phonetic properties. We evaluate its performance on a creative sentence generation task, showing its capability of generating well-formed, catchy and effective sentences that have all the good qualities of slogans produced by human copywriters.
Proceeding IUI '13 Companion Proceedings of the companion publication of the 2013 international conference on Intelligent user interfaces companion Pages 55-56 , 2013
In this paper, we introduce a system that supports the naming process by exploiting natural langu... more In this paper, we introduce a system that supports the naming process by exploiting natural language processing and linguistic creativity techniques in a completely unsupervised fashion. The system generates two types of neologisms based on the category of the service to be named and the properties to be underlined. While the first type consists of homophonic puns and metaphors, the second consists of neologisms that are produced by adding Latin suffixes to English words or homophonic puns. During this process, both semantic appropriateness and sound pleasantness of the generated names are taken into account.
Computational Linguistics and Intelligent Text …, 2013
In this paper, we propose a computational approach to automate the generation of neologisms by ad... more In this paper, we propose a computational approach to automate the generation of neologisms by adding Latin suffixes to English words or homophonic puns. This approach takes into account both semantic appropriateness and sound pleasantness of words. Our analysis of the generated neologisms provides interesting clues for understanding which technologies can successfully be exploited for the task, and the results of the evaluation show that the system that we developed can be a useful tool for supporting the generation of creative names.
Computational Linguistics and Intelligent Text …, 2013
In this paper, we systematically analyze the effect of incorporating different levels of syntacti... more In this paper, we systematically analyze the effect of incorporating different levels of syntactic and semantic information on the accuracy of emotion recognition from text. We carry out the evaluation in a supervised learning framework, and employ tree kernel functions as an intuitive and effective way to generate different feature spaces based on structured representations of the input data. We compare three different formalisms to encode syntactic information enriched with semantic features. These features are obtained from hand-annotated resources as well as distributional models. For the experiments, we use three datasets annotated according to the same set of emotions. Our analysis indicates that shallow syntactic information can positively interact with semantic features. In addition, we show how the three datasets can hardly be combined to learn more robust models, due to inherent differences in the linguistic properties of the texts or in the annotation.
Like its predecessors in 1996 (University of Twente, the Netherlands) and 2002 (ITC-irst, Trento,... more Like its predecessors in 1996 (University of Twente, the Netherlands) and 2002 (ITC-irst, Trento, Italy), this Third International Workshop on Computational Humor (IWCH 2012) focusses on the possibility to find algorithms that allow understanding and generation of humor. There is the general aim of modeling humor, and if we can do that, it will provide us with lots of information about our cognitive abilities in general, such as reasoning, remembering, understanding situations, and understanding conversational partners. But it also provides us with information about being creative, making associations, storytelling and language use. Many more subtleties in face-to-face and multiparty interaction can be added, such as using humor to persuade and dominate, to soften or avoid a face threatening act, to ease a tense situation or to establish a friendly or romantic relationship. One issue to consider is: when is a humorous act appropriate?
Proceedings of the 50th Annual Meeting of the …, 2012
In this paper, we propose a computational approach to generate neologisms consisting of homophoni... more In this paper, we propose a computational approach to generate neologisms consisting of homophonic puns and metaphors based on the category of the service to be named and the properties to be underlined. We describe all the linguistic resources and natural language processing techniques that we have exploited for this task. Then, we analyze the performance of the system that we have developed. The empirical results show that our approach is generally effective and it constitutes a solid starting point for the automation of the naming process.
Abstract The name of a company or a brand is the key element to a successful business. A good nam... more Abstract The name of a company or a brand is the key element to a successful business. A good name is able to state the area of competition and communicate the promise given to customers by evoking semantic associations. Although various resources provide distinct tips for inventing creative names, little research was carried out to investigate the linguistic aspects behind the naming mechanism. Besides, there might be latent methods that copywriters unconsciously use.
Abstract In todaypsilas world, many systems and approaches make it possible for us to be guided b... more Abstract In todaypsilas world, many systems and approaches make it possible for us to be guided by the recommendations they provide. Personalization, which intends to resolve the problems caused by the huge amount of information around, is the main goal to be achieved by these systems. In this paper, we represent the Web based recommendation system that we have developed by using personalization techniques combining machine learning with automated reasoning.
Colors have a very important role on our perception of the world. We often associate colors with ... more Colors have a very important role on our perception of the world. We often associate colors with various concepts at different levels of consciousnes and these associations can be relevant to many fields such as education and advertisement. However, to the best of our knowledge, there are no systematic approaches to aid the automatic development of resources encoding this kind of knowledge. In this paper, we propose three computational methods based on image analysis, language models, and latent semantic analysis to automatically associate colors to words. We compare these methods against a gold standard obtained via crowdsourcing. The results show that each method is effective in capturing different aspects of word-color associations.
Vocabulary acquisition is a very important step for learning a new language. On the other hand, m... more Vocabulary acquisition is a very important step for learning a new language. On the other hand, many learners find this step difficult and time consuming. Several vocabulary teaching methods try to facilitate this step with various verbal and visual tips. However, the preparation of these tips generally necessitates a huge amount of time, money and human labor. In this paper, we propose to exploit Natural Lanugage Processing driven creativity to develop an automatic system for task of vocabulary teaching. This system can automatically generate memorization tips for the words which users would like to memorize. The preliminary results are promising and motivating for further investigation, since they show that our approach can be quite effective on the related task.
This paper aims to shed some light on the concept of virality - especially in social networks - a... more This paper aims to shed some light on the concept of virality - especially in social networks - and to provide new insights on its structure. We argue that: (a) virality is a phe- nomenon strictly connected to the nature of the content being spread, rather than to the influencers who spread it (b) virality is a phenomenon with many facets, i.e. under this generic term several different effects of persuasive communication are comprised and they only partially overlap. To give ground to our claims, we provide initial experiments in a machine learning framework to show how various aspects of virality can be independently predicted according to content features.
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