From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods

Tabular data often refers to data that is organized in a table with rows and columns. We observe that this data format is widely used on the Web and within enterprise data repositories. Tables potentially contain rich semantic information that still needs to be interpreted. The process of extracting meaningful information out of tabular data with respect to a semantic artefact, such as an ontology or a knowledge graph, is often referred to as Semantic Table Interpretation (STI) or Semantic Table Annotation. In this survey paper, we aim to provide a comprehensive and up-to-date state-of-the-art review of the different tasks and methods that have been proposed so far to perform STI. First, we propose a new categorization that reflects the heterogeneity of table types that one can encounter, revealing different challenges that need to be addressed. Next, we define five major sub-tasks that STI deals with even if the literature has mostly focused on three sub-tasks so far. We review and group the many approaches that have been proposed into three macro families and we discuss their performance and limitations with respect to the various datasets and benchmarks proposed by the community. Finally, we detail what are the remaining scientific barriers to be able to truly automatically interpret any type of tables that can be found in the wild Web.     

Tongue-Movement Communication and Control Concept for Hands-Free Human–Machine Interfaces

A new communication and control concept using tongue movements is introduced to generate, detect, and classify signals that can be used in novel hands-free human-machine interface applications such as communicating with a computer and controlling devices. The signals that are caused by tongue movements are the changes in the airflow pressure that occur in the ear canal. The goal is to demonstrate that the ear pressure signals that are acquired using a microphone that is inserted into the ear canal, due to specific tongue movements, are distinct and that the signals can be detected and classified very accurately. The strategy that is developed for demonstrating the concept includes energy-based signal detection and segmentation to extract ear pressure signals due to tongue movements, signal normalization to decrease the trial-to-trial variations in the signals, and pairwise cross-correlation signal averaging to obtain accurate estimates from ensembles of pressure signals. A new decision fusion classification algorithm is formulated to assign the pressure signals to their respective tongue-movement classes. The complete strategy of signal detection and segmentation, estimation, and classification is tested on four tongue movements of eight subjects. Through extensive experiments, it is demonstrated that the ear pressure signals due to the tongue movements are distinct and that the four pressure signals can be classified with an accuracy of more than 97% averaged across the eight subjects using the decision fusion classification algorithm. Thus, it is concluded that, through the unique concept that is introduced in this paper, human-computer interfaces that use tongue movements can be designed for hands-free communication and control applications.     

Is Someone in this Office Available to Help Me?

Robots are increasingly autonomous in our environments, but they still must overcome limited sensing, reasoning, and actuating capabilities while completing services for humans. While some work has focused on robots that proactively request help from humans to reduce their limitations, the work often assumes that humans are supervising the robot and always available to help. In this work, we instead investigate the feasibility of asking for help from humans in the environment who benefit from its services. Unlike other human helpers that constantly monitor a robot’s progress, humans in the environment are not supervisors and a robot must proactively navigate to them to receive help. We contribute a study that shows that several of our environment occupants are willing to help our robot, but, as expected, they have constraints that limit their availability due to their own work schedules. Interestingly, the study further shows that an available human is not always in close proximity to the robot. We present an extended model that includes the availability of humans in the environment, and demonstrate how a navigation planner can incorporate this information to plan paths that increase the likelihood that a robot can find an available helper when it needs one. Finally, we discuss further opportunities for the robot to adapt and learn from the occupants over time.     

Performance implications of information-value offering in e-service systems: Examining the resource-based perspective and innovation strategy

This research examines the performance implications of information-value offering in e-service systems. Specifically, this study introduces both a resource-based perspective that combines technology, human, and business resources to develop an e-service capability, and an innovation strategy that emphasizes service innovation orientation to examine information-value offering. This study also examines how firms bundle e-service capability and service innovation orientation to enhance information-value offering that enhances customer relationships and organizational performance. The results from a survey of 115 financial service firms in Taiwan highlight the importance of how e-service capability and service innovation orientation leads to information-value offering and that this value is shown to positively influence organizational performance by customer relationship performance. The results suggest that researchers and practitioners should pay special attention to the complementary resource-strategy that are needed to successfully implement e-service systems initiatives and that an emphasis on the resource or strategy alone may not be sufficient.     

Design and evaluation of systems to support interaction capture and retrieval

Although many recent systems have been built to support Information Capture and Retrieval (ICR), these have not generally been successful. This paper presents studies that evaluate two different hypotheses for this failure, firstly that systems fail to address user needs and secondly that they provide only rudimentary support for ICR. Having first presented a taxonomy of different systems built to support ICR, we then describe a study that attempts to identify user needs for ICR. On the basis of that study we carried out two user-oriented evaluations. In the first, we carried out a task-based evaluation of a state-of-the-art ICR system, finding that it failed to provide users with abstract ways to view meetings data, and did not present users with information categories that they considered to be important. In a second study, we introduce a new method for comparative evaluation of different techniques for accessing meetings data. The second study showed that simple interface techniques that extracted key information from meetings were effective in allowing users to extract gist from meetings data. We conclude with a discussion of outstanding issues and future directions for ICR research.     

Black Swans,New Nostradamuses,Voodoo decision theories,and the science of decision making in the face of severe uncertainty

The recent global financial crisis, natural disasters, and ongoing debate on global warming and climate change are a stark reminder of the huge challenges that severe uncertainty presents in decision and policy making. My objective in this paper is to look at some of the issues that need to be taken into account in the modeling and analysis of decision problems that are subject to severe uncertainty, paying special attention to some of the misconceptions that are being promulgated in this area. I also examine two diametrically opposed approaches to uncertainty. One, that emphasizes that the difficulties encountered in the modeling, analysis, and solution of decision problems in the face of severe uncertainty are in fact insurmountable, and another that claims to provide, against all odds, a reliable strategy for a successful handling of situations subject to severe uncertainty.     

Simple evolution of complex crystal species

Cairns-Smith has proposed that life began as structural patterns in clays that self-replicated during cycles of crystal growth and fragmentation. Complex, evolved crystal forms could then have catalyzed the formation of a more advanced genetic material. A crucial weakness of this theory is that it is unclear how complex crystals might arise through Darwinian evolution and selection. Here we investigate whether complex crystal patterns could evolve using a model system for crystal growth, DNA tile crystals, that is amenable to both theoretical and experimental inquiry. It was previously shown that in principle, the evolution of crystals assembled from a set of thousands of DNA tile types under very specific environmental conditions could produce arbitrarily complex patterns. Here we show that evolution driven only by the dearth of one monomer type could produce complex crystals from just 12 monomer types. When a monomer type is rare, crystals that use few of this monomer type are selected for. We use explicit enumeration to show that there are situations in which crystal species that use a particular monomer type less frequently will grow faster, yet to do so requires that the information contained in the crystal become more complex. We show that this feature of crystal organization could allow more complex crystal morphologies to be selected for in the right environment, using both analysis in a simple model of self-assembly and stochastic kinetic simulations of crystal growth. The proposed mechanism of evolution is simple enough to test experimentally and is sufficiently general that it may apply to other DNA tile crystals or even to natural crystals, suggesting that complex crystals could evolve from simple starting materials because of relative differences in concentrations of the materials needed for growth.     

IPSec VPN的性能分析

VPN的性能与加密算法，认证算法和网络环境有关。计算表明，加密算法的吞吐量只有认证算法吞吐量的10％－35％，因此，加密算法对VPN性能的影响比认证算法对VPN性能的影响大，提高加密和认证算法的吞吐量，对提高高带宽网络VPN的性能具有明显的效果。     

Hidden symbols: How informal symbolism in digital interfaces disrupts usability for preschoolers

Linking a symbol to the object it represents is a skill that develops gradually over the first few years of life. However, prior work shows that frequent use of this capacity makes it unintuitive for adults to recognize it as a challenge for young children. We hypothesized that this disconnect would manifest in software interfaces designed for young children, such that applications would embed symbols that the target audience would fail to understand. We conducted a randomized controlled trial with 34 preschoolers between the ages of 2 and 5 to assess their ability to work with user interface elements that require symbolic mappings. In particular, we assessed, (1) symbolic progress bars and (2) demonstrations of touch interactions by an on-screen cartoon hand. We found that these techniques are entirely inaccessible for children under 3 and that they require specific design choices to facilitate understanding in children between the ages of 3 and 5. Among a sample of 94 popular apps targeting children in this age range, we found that these symbolic techniques are incorporated into 44% of apps for preschoolers. We further found that embellishing symbolic elements with visual detail, a common practice in apps for preschoolers, increases children׳s cognitive burden and is an additional barrier to performing the symbolic mappings necessary to use these interfaces. We present design alternatives that make these prevalent user interface elements accessible to this user group.     

On "The Right" Software

Boehm[13,37] is credited to have formulated the "Two Rights" of software: the problem of getting the right software and the problem of getting the software right. The development processes needed to achieve software that is right, to us, requires that a proper study of the application domain be done before a serious requirements study is attempted; and to achieve the right software, that is, software that is correct, to us, requires that a proper engineering degree of formalism be applied to the entire development process; that is, that we re-interpret classical development processes[14]. We shall in this paper focus only on the issue of obtaining the right software. In this paper talk we shall outline what we mean by a proper study of the application domain and how it influences the requirements development.     

Generalization to Novel Views: Universal,Class-based,and Model-based Processing

A major problem in object recognition is that a novel image of a given object can be different from all previously seen images. Images can vary considerably due to changes in viewing conditions such as viewing position and illumination. In this paper we distinguish between three types of recognition schemes by the level at which generalization to novel images takes place: universal, class, and model-based. The first is applicable equally to all objects, the second to a class of objects, and the third uses known properties of individual objects. We derive theoretical limitations on each of the three generalization levels. For the universal level, previous results have shown that no invariance can be obtained. Here we show that this limitation holds even when the assumptions made on the objects and the recognition functions are relaxed. We also extend the results to changes of illumination direction. For the class level, previous studies presented specific examples of classes of objects for which functions invariant to viewpoint exist. Here, we distinguish between classes that admit such invariance and classes that do not. We demonstrate that there is a tradeoff between the set of objects that can be discriminated by a given recognition function and the set of images from which the recognition function can recognize these objects. Furthermore, we demonstrate that although functions that are invariant to illumination direction do not exist at the universal level, when the objects are restricted to belong to a given class, an invariant function to illumination direction can be defined. A general conclusion of this study is that class-based processing, that has not been used extensively in the past, is often advantageous for dealing with variations due to viewpoint and illuminant changes.     

Implications of We-Awareness to the Design of Distributed Groupware Tools

We-awareness is the socially recursive inferences that let collaborators know that all are mutually aware of each other’s awareness. While we-awareness is easy afforded in face to face collocated collaboration, it is much more difficult to design distributed groupware tools to provide equivalent capabilities: there can be no awareness unless it is programmed in via system features. We identify a series of questions that must be considered if we-awareness is to be supported. What types of awareness information is crucial and should thus be added to the ‘blank slate’ of a screen sharing system? How can that awareness information be captured through technology, and what information will be lost during this capture process? How should that information be translated, transformed and encoded into a digital form, and—as part of that—what information will be altered as part of that translation process? How will that information be transmitted, and what are the network effects in terms of that information being received in a timely manner? How will that information be represented to other participants in order to enable the rich and subtle interactions that occur in the face-to-face setting? We illustrate the nuances of these questions and why they are difficult to answer by revisiting several prior technical solutions to we-awareness.     

Not by metadata alone: the use of diverse forms of knowledge to locate data for reuse

An important set of challenges for eScience initiatives and digital libraries concern the need to provide scientists with the ability to access data from multiple sources. This paper argues that an analysis of scientists‘ reuse of data prior to the advent of eScience can illuminate the requirements and design of digital libraries and cyberinfrastructure. As part of a larger study on data sharing and reuse, I investigated the processes by which ecologists locate data that were initially collected by others. Ecological data are unusually complex and present daunting problems of interpretation and analysis that must be considered in the design of cyberinfrastructure. The ecologists that I interviewed found ways to overcome many of these difficulties. One part of my results shows that ecologists use formal and informal knowledge that they have gained through disciplinary training and through their own data-gathering experiences to help them overcome hurdles related to finding, acquiring, and validating data collected by others. A second part of my findings reveals that ecologists rely on formal notions of scientific practice that emphasize objectivity to justify the methods they use to collect data for reuse. I discuss the implications of these findings for digital libraries and eScience initiatives.     

Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks

People who show good performance in dynamic complex problem-solving tasks can also make errors. Theories of human error fail to fully explain when and why good performers err. Some theories would predict that these errors are to some extent the consequence of the difficulties that people have in adapting to new and unexpected environmental conditions. However, such theories cannot explain why some new conditions lead to error, while others do not. There are also some theories that defend the notion that good performers are more cognitively flexible and better able to adapt to new environmental conditions. However, the fact is that they sometimes make errors when they face those new conditions. This paper describes one experiment and a research methodology designed to test the hypothesis that when people use a problem-solving strategy, their performance is only affected by those conditions which are relevant to that particular strategy. This hypothesis is derived from theories that explain human performance based on the interaction between cognitive mechanisms and environment.     

Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks

People who show good performance in dynamic complex problem-solving tasks can also make errors. Theories of human error fail to fully explain when and why good performers err. Some theories would predict that these errors are to some extent the consequence of the difficulties that people have in adapting to new and unexpected environmental conditions. However, such theories cannot explain why some new conditions lead to error, while others do not. There are also some theories that defend the notion that good performers are more cognitively flexible and better able to adapt to new environmental conditions. However, the fact is that they sometimes make errors when they face those new conditions. This paper describes one experiment and a research methodology designed to test the hypothesis that when people use a problem-solving strategy, their performance is only affected by those conditions which are relevant to that particular strategy. This hypothesis is derived from theories that explain human performance based on the interaction between cognitive mechanisms and environment.     

Adaptive Optimizing Compilers for the 21st Century

Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This paper describes a prototype system that uses biased random search to discover a program-specific compilation sequence that minimizes an explicit, external objective function. The result is a compiler framework that adapts its behavior to the application being compiled, to the pool of available transformations, to the objective function, and to the target machine. This paper describes experiments that attempt to characterize the space that the adaptive compiler must search. The preliminary results suggest that optimal solutions are rare and that local minima are frequent. If this holds true, biased random searches, such as a genetic algorithm, should find good solutions more quickly than simpler strategies, such as hill climbing.     

Assessment of workload and arm position during different work sequences: a study with portable devices on construction workers

It is recognised that work related shoulder pain is overrepresented among construction workers compared to other occupations. Studies have shown that working with hands above shoulder level increases the shoulder load. Most studies have been confined to the laboratory. The present project was carried out to map the muscular engagement and postures of construction workers undertaking ceiling fitting, and to compare the results to those of the laboratory studies. Two ambulatory devices were used, one allowing recording of electromyographic (EMG) signals bilaterally from the trapezius muscle, and the other to record the position of both arms and back by means of measuring the angles between the vertical line and the back and both upper arms. These recordings were performed during 1.5–2 h work sequences. The results show that the work was mostly performed in an upright position, that both arms were used to a similar amount and that the workers for a large proportion of their working time had their upper arms at levels that are considered harmful in view of shoulder load. The EMG data showed that nearly 50% of the work was spent with trapezius activity that exceeded that of the reference contraction used (about 15% of maximal voluntary contraction) and that the time spent in muscular relaxation was 10%. It was concluded that the exposure of construction workers undertaking ceiling fitting meets the criteria formulated on the basis of laboratory experiments with respect to a high risk of acquiring chronic shoulder pain, due to rotator cuff tendinitis.     

Work-focused analysis and design

The past decade has seen papers in this journal and other cognitive engineering publications expressing concern about some of our foundational ideas. Cognition, a central construct for this journal, is one that some authors would see banished. Function allocation is another. These commentaries, if taken seriously, have the potential to transform our discipline but whether for benefit or detriment is questionable. I review those commentaries in this paper and conclude that the issues raised have merit but that the proposed solutions would be counterproductive, having the potential, if widely implemented, to cripple our discipline. I argue that these commentaries appear credible only because they appeal to an objectivist paradigm as engendered by a techno-centric world view and that they fail to accommodate the inescapable subjectivity of a scientific enterprise. I further argue that these commentaries do not take full account of the fundamental basis of our discipline; that it is an analysis and design discipline and that it is first and foremost human centric. Our discipline requires a work-focused perspective. We need to think seriously about what that means, and we need to deploy language and methods that are entirely consistent with a work-focused stance.     

Can We Ever Escape from Data Overload? A Cognitive Systems Diagnosis

Data overload is a generic and tremendously difficult problem that has only grown with each new wave of technological capabilities. As a generic and persistent problem, three observations are in need of explanation: Why is data overload so difficult to address? Why has each wave of technology exacerbated, rather than resolved, data overload? How are people, as adaptive responsible agents in context, able to cope with the challenge of data overload? In this paper, first we examine three different characterisations that have been offered to capture the nature of the data overload problem and how they lead to different proposed solutions. As a result, we propose that (a) data overload is difficult because of the context sensitivity problem – meaning lies, not in data, but in relationships of data to interests and expectations and (b) new waves of technology exacerbate data overload when they ignore or try to finesse context sensitivity. The paper then summarises the mechanisms of human perception and cognition that enable people to focus on the relevant subset of the available data despite the fact that what is interesting depends on context. By focusing attention on the root issues that make data overload a difficult problem and on people’s fundamental competence, we have identified a set of constraints that all potential solutions must meet. Notable among these constraints is the idea that organisation precedes selectivity. These constraints point toward regions of the solution space that have been little explored. In order to place data in context, designers need to display data in a conceptual space that depicts the relationships, events and contrasts that are informative in a field of practice.