Surveying human habit modeling and mining techniques in smart spaces

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field

Inference in classifier systems

Classifier systems (Css) provide a rich framework for learning and induction, and they have beenı successfully applied in the artificial intelligence literature for some time. In this paper, both theı architecture and the inferential mechanisms in general CSs are reviewed, and a number of limitations and extensions of the basic approach are summarized. A system based on the CS approach that is capable of quantitative data analysis is outlined and some of its peculiarities discussed

Classifying and completing word analogies by machine learning

Analogical proportions are statements of the form ‘a is to b as c is to d’, formally denoted a:b::c:d. They are the basis of analogical reasoning which is often considered as an essential ingredient of human intelligence. For this reason, recognizing analogies in natural language has long been a research focus within the Natural Language Processing (NLP) community. With the emergence of word embedding models, a lot of progress has been made in NLP, essentially assuming that a word analogy like man:king::woman:queen is an instance of a parallelogram within the underlying vector space. In this paper, we depart from this assumption to adopt a machine learning approach, i.e., learning a substitute of the parallelogram model. To achieve our goal, we first review the formal modeling of analogical proportions, highlighting the properties which are useful from a machine learning perspective. For instance, the postulates supposed to govern such proportions entail that when a:b::c:d holds, then seven permutations of a,b,c,d still constitute valid analogies. From a machine learning perspective, this provides guidelines to build training sets of positive and negative examples. Taking into account these properties for augmenting the set of positive and negative examples, we first implement word analogy classifiers using various machine learning techniques, then we approximate by regression an analogy completion function, i.e., a way to compute the missing word when we have the three other ones. Using a GloVe embedding, classifiers show very high accuracy when recognizing analogies, improving state of the art on word analogy classification. Also, the regression processes usually lead to much more successful analogy completion than the ones derived from the parallelogram assumption. © 202

Analogical classification in formal grammar

The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon

Analogical classification in formal grammar

The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon

Analogical classification in formal grammar

The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon

Analogical classification in formal grammar

The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon

Analogical classification in formal grammar

The organization of the lexicon, and especially the relations between groups of lexemes is a strongly debated topic in linguistics. Some authors have insisted on the lack of any structure of the lexicon. In this vein, Di Sciullo & Williams (1987: 3) claim that “[t]he lexicon is like a prison – it contains only the lawless, and the only thing that its inmates have in commonis lawlessness”. In the alternative view, the lexicon is assumed to have a rich structure that captures all regularities and partial regularities that exist between lexical entries.Two very different schools of linguistics have insisted on the organization of the lexicon. On the one hand, for theories like HPSG (Pollard & Sag 1994), but also some versions of construction grammar (Fillmore & Kay 1995), the lexicon is assumed to have a very rich structure which captures common grammatical properties between its members. In this approach, a type hierarchy organizes the lexicon according to common properties between items. For example, Koenig (1999: 4, among others), working from an HPSG perspective, claims that the lexicon “provides a unified model for partial regularties, medium-size generalizations, and truly productive processes”. On the other hand, from the perspective of usage-based linguistics, several authors have drawn attention to the fact that lexemes which share morphological or syntactic properties, tend to be organized in clusters of surface (phonological or semantic) similarity (Bybee & Slobin 1982; Skousen 1989; Eddington 1996). This approach, often called analogical, has developed highly accurate computational and non-computational models that can predict the classes to which lexemes belong. Like the organization of lexemes in type hierarchies, analogical relations between items help speakers to make sense of intricate systems, and reduce apparent complexity (Köpcke & Zubin 1984). Despite this core commonality, and despite the fact that most linguists seem to agree that analogy plays an important role in language, there has been remarkably little work on bringing together these two approaches. Formal grammar traditions have been very successful in capturing grammatical behaviour, but, in the process, have downplayed the role analogy plays in linguistics (Anderson 2015). In this work, I aim to change this state of affairs. First, by providing an explicit formalization of how analogy interacts with grammar, and second, by showing that analogical effects and relations closely mirror the structures in the lexicon. I will show that both formal grammar approaches, and usage-based analogical models, capture mutually compatible relations in the lexicon