ppxscal/embedding_network huggingface dataset:
RHB+: a type-oriented ILP system learning from positive data
Authors: Yutaka Sasaki, Masahiko Haruno
Venue: Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2 (1997)

This paper presents the type-oriented relational learner RHB+. Attaching type information to hypotheses is effective in avoiding overgeneralization as well as enhancing readability and comprehensibility. In many areas, such as NLP, type information is actually available, while negative examples are not. Unfortunately, learning performance is usually poor if types are attached when only positive examples are available. RHB+ makes use of type information to efficiently compute informativity from positive examples only and to judge a stopping condition. The new technique of dynamic type restriction by positive examples lets covered positive examples decide the types appropriate for the current clause. The current version of RHB+, written in the typed logic programming language LIFE, directly manipulates types as structured background knowledge when operations related to types are required. These features make RHB+ efficient and effective in attaching types selected from thousands of possible types. This leads to advantages over several previous learners, such as FOIL and PROGOL. Experimental results demonstrate RHB+ 's fine performance for both artificial and real data.
Properties of programs with monotone and convex constraints
Authors: Lengning Liu, Mirosław Truszczynski
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 2 (2005)

We study properties of programs with monotone and convex constraints. We extend to these formalisms concepts and results from normal logic programming. They include tight programs and Fages Lemma, program completion and loop formulas, and the notions of strong and uniform equivalence with their characterizations. Our results form an abstract account of properties of some recent extensions of logic programming with aggregates, especially the formalism of smodels.
Adhoc and Book XML Retrieval with Cheshire
Authors: Ray R. Larson
Venue: Advances in Focused Retrieval: 7th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2008, Dagstuhl Castle, Germany, December 15-18, 2008. Revised and Selected Papers (2009)

For this year's INEX UC Berkeley focused on the Book track and also submitted two runs for the Adhoc Focused Element search task and one for the Best in Context task. For all of these runs we used the TREC2 logistic regression probabilistic model. For the Adhoc Element runs and Best in Context runs we used the "pivot" score merging method to combine paragraph-level searches with scores for document-level searches.
Reconstructing Microwave Near-Field Image Based on the Discrepancy of Radial Distribution of Dielectric Constant
Authors: Zhifu Tao, Qifeng Pan, Meng Yao, Ming Li
Venue: Proceedings of the International Conference on Computational Science and Its Applications: Part I (2009)

Based on the difference of dielectric properties between normal breast tissues and malignant tumors, microwave scatter-sounding method is used to detect the breast then get the projection reconstruction data. With the characteristics of radial distribution of the data, dielectric property of the detected space is reconstructed. In this paper, not only the microwave near-field imaging model is discussed in detail, but also the reconstruction result. The effectiveness of this method has been approved by the reconstruction result of some typical detected spaces.
Multi-Optimisation Consensus Clustering
Authors: Jian Li, Stephen Swift, Xiaohui Liu
Venue: Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII (2009)

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.
Re-ranking models for spoken language understanding
Authors: Marco Dinarelli, Alessandro Moschitti, Giuseppe Riccardi
Venue: Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (2009)

Spoken Language Understanding aims at mapping a natural language spoken sentence into a semantic representation. In the last decade two main approaches have been pursued: generative and discriminative models. The former is more robust to overfitting whereas the latter is more robust to many irrelevant features. Additionally, the way in which these approaches encode prior knowledge is very different and their relative performance changes based on the task. In this paper we describe a machine learning framework where both models are used: a generative model produces a list of ranked hypotheses whereas a discriminative model based on structure kernels and Support Vector Machines, re-ranks such list. We tested our approach on the MEDIA corpus (human-machine dialogs) and on a new corpus (human-machine and human-human dialogs) produced in the European LUNA project. The results show a large improvement on the state-of-the-art in concept segmentation and labeling.
Neural substrates of visuospatial processing in distinct reference frames: Evidence from unilateral spatial neglect
Authors: Jared Medina, Vijay Kannan, Mikolaj A. Pawlak, Jonathan T. Kleinman, Melissa Newhart, Cameron Davis, Jennifer E. Heidler-Gary, Edward H. Herskovits, Argye E. Hillis
Venue: Journal of Cognitive Neuroscience (2009)

There is evidence for different levels of visuospatial processing with their own frames of reference: viewer-centered, stimulus-centered, and object-centered. The neural locus of these levels can be explored by examining lesion location in subjects with unilateral spatial neglect (USN) manifest in these reference frames. Most studies regarding the neural locus of USN have treated it as a homogenous syndrome, resulting in conflicting results. In order to further explore the neural locus of visuospatial processes differentiated by frame of reference, we presented a battery of tests to 171 subjects within 48 hr after right supratentorial ischemic stroke before possible structural and/or functional reorganization. The battery included MR perfusion weighted imaging (which shows hypoperfused regions that may be dysfunctional), diffusion weighted imaging (which reveals areas of infarct or dense ischemia shortly after stroke onset), and tests designed to disambiguate between various types of neglect. Results were consistent with a dorsal/ventral stream distinction in egocentric/allocentric processing. We provide evidence that portions of the dorsal stream of visual processing, including the right supramarginal gyrus, are involved in spatial encoding in egocentric coordinates, whereas parts of the ventral stream (including the posterior inferior temporal gyrus) are involved in allocentric encoding.
Fast Cryptographic Primitives and Circular-Secure Encryption Based on Hard Learning Problems
Authors: Benny Applebaum, David Cash, Chris Peikert, Amit Sahai
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

The well-studied task of learning a linear function with errors is a seemingly hard problem and the basis for several cryptographic schemes. Here we demonstrate additional applications that enjoy strong security properties and a high level of efficiency. Namely, we construct: 1 Public-key and symmetric-key cryptosystems that provide security for key-dependent messages and enjoy circular security. Our schemes are highly efficient: in both cases the ciphertext is only a constant factor larger than the plaintext, and the cost of encryption and decryption is only n·polylog(n) bit operations per message symbol in the public-key case, and polylog(n) bit operations in the symmetric-case. 1 Two efficient pseudorandom objects: a "weak randomized pseudorandom function" -- a relaxation of standard PRF -- that can be computed obliviously via a simple protocol, and a length-doubling pseudorandom generator that can be computed by a circuit of n ·polylog(n) size. The complexity of our pseudorandom generator almost matches the complexity of the fastest known construction (Applebaum et al., RANDOM 2006), which runs in linear time at the expense of relying on a nonstandard intractability assumption. Our constructions and security proofs are simple and natural, and involve new techniques that may be of independent interest. In addition, by combining our constructions with prior ones, we get fast implementations of several other primitives and protocols.
Building a BioWordNet by using WordNet's data formats and WordNet's software infrastructure: a failure story
Authors: Michael Poprat, Elena Beisswanger, Udo Hahn
Venue: Software Engineering, Testing, and Quality Assurance for Natural Language Processing (2008)

In this paper, we describe our efforts to build on WordNet resources, using WordNet lexical data, the data format that it comes with and WordNet's software infrastructure in order to generate a biomedical extension of WordNet, the BioWordNet. We began our efforts on the assumption that the software resources were stable and reliable. In the course of our work, it turned out that this belief was far too optimistic. We discuss the stumbling blocks that we encountered, point out an error in the WordNet software with implications for research based on it, and conclude that building on the legacy of WordNet data structures and its associated software might preclude sustainable extensions that go beyond the domain of general English.
Application of Fuzzy Mathematics Assessment to Groundwater Quality in Jining City
Authors: Juan Zhang, Changjun Zhu
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

The water quality of groundwater in Jining has been assessed comprehensively based on the environmental investigation and monitoring in order to provide the scientific basis for the pollution treatment in the Jining city. This paper discussed the choice of the evaluated factors, the operations of the weight value, and compares with the status of the water quality in the course of the evaluation. The conclusions indicated that the result of the fuzzy mathematics evaluation represented the water quality of groundwater in Jining city. The evaluation result was compared with that of the traditional method and the reported results in Jining. It is indicated that the performance of the proposed model is practically feasible in the application of groundwater quality assessment and its application is simple.
Learning MATLAB
Authors: Tobin A. Driscoll
Venue:  (2009)

This engaging book is a very compact introduction to the essentials of the MATLAB programming language and is ideal for readers seeking a focused and brief approach to the software. Learning MATLAB contains numerous examples and exercises involving the software s most useful and sophisticated features along with an overview of the most common scientific computing tasks for which it can be used. The presentation is designed to guide new users through the basics of interacting with and programming in the MATLAB software, while also presenting some of its more important and advanced techniques, including how to solve common problem types in scientific computing. Rather than including exhaustive technical material, the author teaches through readily understood examples and numerous exercises that range from straightforward to very challenging. Readers are encouraged to learn by doing: entering the examples themselves, reading the online help, and trying the exercises. Audience: This handbook is suitable for graduate students, advanced undergraduate students, and professional researchers in mathematics, scientific computing, and application areas in science and engineering. It can be used as the primary text for a short course, as a companion textbook for a numerical computing course, or for self-study. Contents: List of Figures; List of Tables; Preface; Chapter 1: Introduction; Chapter 2: Arrays and Matrices; Chapter 3: Scripts and Functions; Chapter 4: More on Functions; Chapter 5: Graphics; Chapter 6: Advanced Techniques; Chapter 7: Scientific Computing; Afterword; Index.
Normalizing Biomedical Name Entities by Similarity-Based Inference Network and De-ambiguity Mining
Authors: Chih-Hsuan Wei, I-Chin Huang, Yi-Yu Hsu, Hung-Yu Kao
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

To construct an intelligent biomedical knowledge management system, researchers had proposed many relation extraction methods in past. Before applying these methods, the system has to recognize the name entities in the literature and map the entities to the relative EntrezIDs. The purpose of this study is to automatically and exactly identify the relative EntrezIDs which are mentioned in literatures. We employ the similarity-based inference network to calculate the similarity score with the entities, and this EntrezID is a solution to the term variation problem. The proposed de-ambiguity strategy increases the confidence of EntrezID in literature. The strategy provides researchers a good utilization of information for mapping the entity to the EntrezID. As a result, the precision of system increase about 75.1%, and it makes the identified entity even more meaningful. The system using the proposed strategies outperforms the previous methods in biomedical entity normalization.
Global Sourcing of Software Development - A Review of Tools and Services
Authors: Robert Martignoni
Venue: Proceedings of the 2009 Fourth IEEE International Conference on Global Software Engineering (2009)

Software services in a globally distributed environment face signiﬁcant management challenges. All phases of the software life-cycle need to be aligned to the distributed development environment. This challenge has been led to the development of a variety of tools and services. This paper identiﬁes tools and services aiming at the optimisation of the globally distributed software development. Software-as-a-service seems to be a promising approach to optimise the globally distributed software development. The characteristics and advantages of Software-as-a-service in regards to globally distributed software development are discussed. The paper concludes with a closing discussion of the identiﬁed tools and services. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Genetic Algorithm for the Design of Confronting Two-Pair Primers
Authors: Cheng-Hong Yang, Yu-Huei Cheng, Li-Yeh Chuang, Hsueh-Wei Chang
Venue: Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering (2009)

Many single nucleotide polymorphisms (SNPs) genotyping techniques have been developed but most of them are expensive. Polymerase chain reaction with confronting two-pair primers (PCR-CTPP) is a restriction enzyme-free and economic genotyping but its primer design is still computationally challenged. Here, we introduced a genetic algorithm (GA)-based PCR-CTPP primer design method. Thirty SNPs of the Janus kinase 2 gene with their SNP flanking length for 500 bps were tested. These GA-based designing CTPP primers were characterized with close values for melting temperature (Tm) and specificity, and their corresponding PCR products were provided with the optimal length. In conclusion, this novel PCR-CTPP primer designing method provides the computation for the primer information of cost- and time-effective enzyme-free SNP genotyping.
Word sense disambiguation with semi-supervised learning
Authors: Thanh Phong Pham, Hwee Tou Ng, Wee Sun Lee
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Current word sense disambiguation (WSD) systems based on supervised learning are still limited in that they do not work well for all words in a language. One of the main reasons is the lack of sufficient training data. In this paper, we investigate the use of unlabeled training data for WSD, in the framework of semi-supervised learning. Four semisupervised leaming algorithms are evaluated on 29 nouns of Senseval-2 (SE2) English lexical sample task and SE2 English all-words task. Empirical results show that unlabeled data can bring significant improvement in WSD accuracy.
Searching for common sense: populating Cyc™ from the web
Authors: Cynthia Matuszek, Michael Witbrock, Robert C. Kahlert, John Cabral, Dave Schneider, Purvesh Shah, Doug Lenat
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

The Cyc project is predicated on the idea that effective machine learning depends on having a core of knowledge that provides a context for novel learned information - what is known informally as "common sense." Over the last twenty years, a sufficient core of common sense knowledge has been entered into Cyc to allow it to begin effectively and flexibly supporting its most important task: increasing its own store of world knowledge. In this paper, we present initial work on a method of using a combination of Cyc and the World Wide Web, accessed via Google, to assist in entering knowledge into Cyc. The long-term goal is automating the process of building a consistent, formalized representation of the world in the Cyc knowledge base via machine learning. We present preliminary results of this work and describe how we expect the knowledge acquisition process to become more accurate, faster, and more automated in the future.
Community-base Fault Diagnosis Using Incremental Belief Revision
Authors: Yongning Tang, Guang Cheng, Zhiwei Xu, Ehab Al-Shaer
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

Overlay networks have emerged as a powerful and flexible platform for developing new disruptive network applications. The attractive characteristics of overlay networks such as planetary-scale distributions, user-level flexibility (e.g., overlay routing) and manageability bring to overlay fault diagnosis new challenges, which include inaccessible underlying network information, incomplete and inaccurate network status observations; dynamic symptom-fault causality relationships, and multi-layer complexity. To address these challenges, we propose a distributed user-level Belief Revision based overlay fault diagnosis technique called EUDiag. EUDiag can passively use observed overlay symptoms as reported by overlay monitoring agents to correlate and diagnose faults, and select the least-costly appropriate probing actions whenever necessary to enhance the passive fault reasoning results. EUDiag adapts to the changes in highly dynamic overlay networks by incrementally revising user beliefs based on new observed overlay symptoms. EUDiag can diagnose faults without relying on underlying network fault probabilistic quantifications (e.g. prior fault probability).Simulations and experimental studies show that EUDiag can efficiently (e.g. low latency) and accurately localize root causes of overlay faults/problems, even when the observed symptoms are incomplete.
Improving Responsiveness of Hard Real-Time Embedded Systems
Authors: Hugh Anderson, Siau-Cheng Khoo
Venue: Proceedings of the 2009 Third IEEE International Symposium on Theoretical Aspects of Software Engineering (2009)

Abstract--- Hard real-time systems are found in many critical embedded applications, for example aeroplane flight control, industrial production line control, and so on. The safe scheduling of tasks in these hard real-time systems is crucial to their correct operation, but the hard constraints of this type of scheduling reduce the responsiveness of the systems. In this paper we show the application of runtime analysis in informing the design of hard real-time embedded systems by allowing scheduled tasks to be dynamically re-ordered to improve the average responsiveness, while still meeting the hard constraints imposed by the system. The technique is semi-automated, and uses the reduce computer algebra system to precalculate a symbolic form of the runtime of scheduled tasks. The symbolic form is used to modify the source code of the scheduler.
Gamers against All Odds
Authors: Anna-Sofia Alklind Taylor, Per Backlund, Henrik Engström, Mikael Johannesson, Mikael Lebram
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

The goal of the project presented in this paper is to enable motor rehabilitation to stroke patients in their home environment and to utilise game enjoyment to achieve frequent training. Stroke patients have an average age above 70 years, which implies that they typically do not belong to a gaming generation. In addition, these patients suffer from motor, and many times cognitive impairments, which make traditional games extremely difficult to use. Nearly all work in this area has been conducted in a clinic environment where it is possible to overcome some of these difficulties by letting professionals assist and guide patients.In this paper, we present the challenges faced, the system itself and the result from a study where five patients were equipped with a game console in their homes for five weeks. The focus of this paper is on analysing the gaming behaviour of patients, which includes the amount of time they spent, the type of games they selected and their comments on the gaming experience. The conclusion from this analysis is that their behaviour resembles that of gamers. They spent significant voluntary time, and it has been possible for patients, with no prior experience of computer games, to enjoy gaming in their homes where they had no professional assistance.
Expressive negotiation in settings with externalities
Authors: Vincent Conitzer, Thomas Sandholm
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

In recent years, certain formalizations of combinatorial negotiation settings, most notably combinatorial auctions, have become an important research topic in the AI community. A pervasive assumption has been that of no externalities: the agents deciding on a variable (such as whether a trade takes place between them) are the only ones affected by how this variable is set. To date, there has been no widely studied formalization of combinatorial negotiation settings with externalities. In this paper, we introduce such a formalization. We show that in a number of key special cases, it is NP-complete to find a feasible nontrivial solution (and therefore the maximum social welfare is completely inapproximable). However, for one important special case, we give an algorithm which converges to the solution with the maximal concession by each agent (in a linear number of rounds for utility functions that decompose into piecewise constant functions). Maximizing social welfare, however, remains NP-complete even in this setting. We also demonstrate a special case which can be solved in polynomial time by linear programming.