4,683 research outputs found
Wrapper Maintenance: A Machine Learning Approach
The proliferation of online information sources has led to an increased use
of wrappers for extracting data from Web sources. While most of the previous
research has focused on quick and efficient generation of wrappers, the
development of tools for wrapper maintenance has received less attention. This
is an important research problem because Web sources often change in ways that
prevent the wrappers from extracting data correctly. We present an efficient
algorithm that learns structural information about data from positive examples
alone. We describe how this information can be used for two wrapper maintenance
applications: wrapper verification and reinduction. The wrapper verification
system detects when a wrapper is not extracting correct data, usually because
the Web source has changed its format. The reinduction algorithm automatically
recovers from changes in the Web source by identifying data on Web pages so
that a new wrapper may be generated for this source. To validate our approach,
we monitored 27 wrappers over a period of a year. The verification algorithm
correctly discovered 35 of the 37 wrapper changes, and made 16 mistakes,
resulting in precision of 0.73 and recall of 0.95. We validated the reinduction
algorithm on ten Web sources. We were able to successfully reinduce the
wrappers, obtaining precision and recall values of 0.90 and 0.80 on the data
extraction task
Attention and Visibility in an Information Rich World
As the rate of content production grows, we must make a staggering number of
daily decisions about what information is worth acting on. For any flourishing
online social media system, users can barely keep up with the new content
shared by friends. How does the user-interface design help or hinder users'
ability to find interesting content? We analyze the choices people make about
which information to propagate on the social media sites Twitter and Digg. We
observe regularities in behavior which can be attributed directly to cognitive
limitations of humans, resulting from the different visibility policies of each
site. We quantify how people divide their limited attention among competing
sources of information, and we show how the user-interface design can mediate
information spread.Comment: Appearing in 2nd International Workshop on Social Multimedia Research
2013, in conjunction with IEEE International Conference on Multimedia & Expo
(ICME 2013
ΠΠΎΠ³Π½ΠΈΡΠΈΠ²Π½ΠΈ ΠΏΡΠΎΡΠ΅ΡΠΈ, Π΅ΠΌΠΎΡΠΈΠΈ ΠΈ ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠ½ΠΈ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΡΡΠΈ
Π‘ΡΡΠ΄ΠΈΡΠ°ΡΠ° ΠΏΡΠ΅Π·Π΅Π½ΡΠΈΡΠ° ΠΈΡΡΡΠ°ΠΆΡΠ²Π°ΡΠ° ΠΎΠ΄ ΠΏΠΎΠ²Π΅ΡΠ΅ Π½Π°ΡΡΠ½ΠΈ Π΄ΠΈΡΡΠΈΠΏΠ»ΠΈΠ½ΠΈ, ΠΊΠ°ΠΊΠΎ Π²Π΅ΡΡΠ°ΡΠΊΠ° ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠΈΡΠ°, Π½Π΅Π²ΡΠΎΠ½Π°ΡΠΊΠΈ, ΠΏΡΠΈΡ
ΠΎΠ»ΠΎΠ³ΠΈΡΠ°, Π»ΠΈΠ½Π³Π²ΠΈΡΡΠΈΠΊΠ° ΠΈ ΡΠΈΠ»ΠΎΠ·ΠΎΡΠΈΡΠ°, ΠΊΠΎΠΈ ΠΈΠΌΠ°Π°Ρ ΠΏΠΎΡΠ΅Π½ΡΠΈΡΠ°Π» Π·Π° ΠΊΡΠ΅ΠΈΡΠ°ΡΠ΅ Π½Π° ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠ½ΠΈ Π°Π½ΡΡΠΎΠΏΠΎΠΌΠΎΡΡΠ½ΠΈ Π°Π³Π΅Π½ΡΠΈ ΠΈ ΠΈΠ½ΡΠ΅ΡΠ°ΠΊΡΠΈΠ²Π½ΠΈ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ. Π‘Π΅ ΡΠ°Π·Π³Π»Π΅Π΄ΡΠ²Π°Π°Ρ ΡΠΈΡΡΠ΅ΠΌΠΈΡΠ΅ ΠΎΠ΄ ΡΠΈΠΌΠ±ΠΎΠ»ΠΈΡΠΊΠ° ΠΈ ΠΊΠΎΠ½Π΅ΠΊΡΠΈΠΎΠ½ΠΈΡΡΠΈΡΠΊΠ° Π²Π΅ΡΡΠ°ΡΠΊΠ° ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠΈΡΠ° Π·Π° ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠ°ΡΠ΅ Π½Π° ΡΠΎΠ²Π΅ΠΊΠΎΠ²ΠΈΡΠ΅ ΠΊΠΎΠ³Π½ΠΈΡΠΈΠ²Π½ΠΈ ΠΏΡΠΎΡΠ΅ΡΠΈ, ΠΌΠΈΡΠ»Π΅ΡΠ΅, Π΄ΠΎΠ½Π΅ΡΡΠ²Π°ΡΠ΅ ΠΎΠ΄Π»ΡΠΊΠΈ, ΠΌΠ΅ΠΌΠΎΡΠΈΡΠ° ΠΈ ΡΡΠ΅ΡΠ΅. Π‘Π΅ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠ°Π°Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠ΅ Π²ΠΎ Π²Π΅ΡΡΠ°ΡΠΊΠ° ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠΈΡΠ° ΠΈ ΡΠΎΠ±ΠΎΡΠΈΠΊΠ° ΠΊΠΎΠΈ ΠΊΠΎΡΠΈΡΡΠ°Ρ Π΅ΠΌΠΎΡΠΈΠΈ ΠΊΠ°ΠΊΠΎ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·Π°ΠΌ Π·Π° ΠΊΠΎΠ½ΡΡΠΎΠ»Π° Π½Π° ΠΎΡΡΠ²Π°ΡΡΠ²Π°ΡΠ΅ Π½Π° ΡΠ΅Π»ΠΈΡΠ΅ Π½Π° ΡΠΎΠ±ΠΎΡΠΎΡ, ΠΊΠ°ΠΊΠΎ ΡΠ΅Π°ΠΊΡΠΈΡΠ° Π½Π° ΠΎΠ΄ΡΠ΅Π΄Π΅Π½ΠΈ ΡΠΈΡΡΠ°ΡΠΈΠΈ, Π·Π° ΠΎΠ΄ΡΠΆΡΠ²Π°ΡΠ΅ Π½Π° ΠΏΡΠΎΡΠ΅ΡΠΎΡ Π½Π° ΡΠΎΡΠΈΡΠ°Π»Π½Π° ΠΈΠ½ΡΠ΅ΡΠ°ΠΊΡΠΈΡΠ° ΠΈ Π·Π° ΡΠΎΠ·Π΄Π°Π²Π°ΡΠ΅ Π½Π° ΠΏΠΎΡΠ²Π΅ΡΠ»ΠΈΠ²ΠΈ Π°Π½ΡΡΠΎΠΏΠΎΡΠΌΡΠ½ΠΈ Π°Π³Π΅Π½ΡΠΈ.
ΠΡΠ΅Π·Π΅Π½ΡΠΈΡΠ°Π½ΠΈΡΠ΅ ΠΈΠ½ΡΠ΅ΡΠ΄ΠΈΡΡΠΈΠΏΠ»ΠΈΠ½Π°ΡΠ½ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈ ΡΠ΅ ΠΌΠΎΡΠΈΠ²Π°ΡΠΈΡΠ° Π·Π° ΡΠΎΠ·Π΄Π°Π²Π°ΡΠ΅ Π½Π° Π°Π½ΠΈΠΌΠΈΡΠ°Π½ΠΈ Π°Π³Π΅Π½ΡΠΈ ΠΊΠΎΠΈ ΠΊΠΎΡΠΈΡΡΠ°Ρ Π³ΠΎΠ²ΠΎΡ, Π³Π΅ΡΡΠΎΠ²ΠΈ, ΠΈΠ½ΡΠΎΠ½Π°ΡΠΈΡΠ° ΠΈ Π΄ΡΡΠ³ΠΈ Π½Π΅Π²Π΅ΡΠ±Π°Π»Π½ΠΈ ΠΌΠΎΠ΄Π°Π»ΠΈΡΠ΅ΡΠΈ ΠΏΡΠΈ ΠΊΠΎΠ½Π²Π΅ΡΠ·Π°ΡΠΈΡΠ° ΡΠΎ ΠΊΠΎΡΠΈΡΠ½ΠΈΡΠΈΡΠ΅ Π²ΠΎ ΠΈΠ½ΡΠ΅Π»ΠΈΠ³Π΅Π½ΡΠ½ΠΈΡΠ΅ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΡΡΠΈ
Generating socially appropriate tutorial dialog
Analysis of student-tutor coaching dialogs suggest that good human tutors attend to and attempt to influence the motivational state of learners. Moreover, they are sensitive to the social face of the learner, and seek to mitigate the potential face threat of their comments. This paper describes a dialog generator for pedagogical agents that takes motivation and face threat factors into account. This enables the agent to interact with learners in a socially appropriate fashion, and foster intrinsic motivation on the part of the learner, which in turn may lead to more positive learner affective states
On MAS Scalability
In open dynamic multi-agent environments the number of agents can vary significantly within very short periods of time. Very few (if any) current multi-agent systems have, however, been designed to cope with large-scale distributed applications. Scalability requires increasing numbers of new agents and resources to have no noticeable effect on performance nor to increase administrative complexity. In this paper a number of implications for techniques and management are discussed. Current research on agent middleware is briefly described.
The Contribution of Society to the Construction of Individual Intelligence
It is argued that society is a crucial factor in the construction of individual intelligence. In other words that it is important that intelligence is socially situated in an analogous way to the physical situation of robots. Evidence that this may be the case is taken from developmental linguistics, the social intelligence hypothesis, the complexity of society, the need for self-reflection and autism. The consequences for the development of artificial social agents is briefly considered. Finally some challenges for research into socially situated intelligence are highlighted
Modelling Adaptation through Social Allostasis: Modulating the Effects of Social Touch with Oxytocin in Embodied Agents
Social allostasis is a mechanism of adaptation that permits individuals to dynamically adapt their physiology to changing physical and social conditions. Oxytocin (OT) is widely considered to be one of the hormones that drives and adapts social behaviours. While its precise effects remain unclear, two areas where OT may promote adaptation are by affecting social salience, and affecting internal responses of performing social behaviours. Working towards a model of dynamic adaptation through social allostasis in simulated embodied agents, and extending our previous work studying OT-inspired modulation of social salience, we present a model and experiments that investigate the effects and adaptive value of allostatic processes based on hormonal (OT) modulation of affective elements of a social behaviour. In particular, we investigate and test the effects and adaptive value of modulating the degree of satisfaction of tactile contact in a social motivation context in a small simulated agent society across different environmental challenges (related to availability of food) and effects of OT modulation of social salience as a motivational incentive. Our results show that the effects of these modulatory mechanisms have different (positive or negative) adaptive value across different groups and under different environmental circumstance in a way that supports the context-dependent nature of OT, put forward by the interactionist approach to OT modulation in biological agents. In terms of simulation models, this means that OT modulation of the mechanisms that we have described should be context-dependent in order to maximise viability of our socially adaptive agents, illustrating the relevance of social allostasis mechanisms.Peer reviewedFinal Published versio
An MPEG-7 scheme for semantic content modelling and filtering of digital video
Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users
- β¦