Databases and Information Systems Commons^™

Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Polarity classification of opinionated sentences with both positive and negative sentiments1 is a key challenge in sentiment analysis. This paper presents a novel unsupervised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cuephrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsupervised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental …

Trust Network Inference For Online Rating Data Using Generative Models, Freddy Tat Chua Chua, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In an online rating system, raters assign ratings to objects contributed by other users. In addition, raters can develop trust and distrust on object contributors depending on a few rating and trust related factors. Previous study has shown that ratings and trust links can influence each other but there has been a lack of a formal model to relate these factors together. In this paper, we therefore propose Trust Antecedent Factor (TAF)Model, a novel probabilistic model that generate ratings based on a number of rater’s and contributor’s factors. We demonstrate that parameters of the model can be learnt by Collapsed …

An Information Technology (It) Based Approach For Enhancing Prompt And Effective Post-Disaster Reconstruction, Faisal Manzoor Arain

Business Review

Information technology (IT) has become strongly established as a supporting tool for many professional tasks in recent years. One application of IT, namely the knowledge management system, has attracted significant attention requiring further exploration as it has the potential to enhance processes, based on the expertise of the decision-makers. A knowledge management system can undertake intelligent tasks in a specific domain that is normally performed by highly skilled people. Typically, the success of such a system relies on the ability to represent the knowledge for a particular subject. Post-disaster reconstruction and rehabilitation is a complex issue with several dimensions. Government, …

Smob: The Best Of Both Worlds, Alexandre Passant, Julia Anaya, Owen Sacco, Pavan Kapanipathi

Kno.e.sis Publications

This paper presents the architecture of SMOB and the way it combines Semantic Web standards (RDF(S) / SPARQL) and new protocols such as PubSubHubbub to enable a Federated and Privacy-Aware Social Web.

Automatic Domain Model Creation Using Pattern-Based Fact Extraction, Christopher Thomas, Pankaj Mehra, Wenbo Wang, Amit P. Sheth, Gerhard Weikum, Victor Chan

Kno.e.sis Publications

This paper describes a minimally guided approach to automatic domain model creation. The first step is to carve an area of interest out of the Wikipedia hierarchy based on a simple query or other starting point. The second step is to connect the concepts in this domain hierarchy with named relationships. A starting point is provided by Linked Open Data, such as DBPedia. Based on these community-generated facts we train a pattern-based fact-extraction algorithm to augment a domain hierarchy with previously unknown relationship occurrences. Pattern vectors are learned that represent occurrences of relationships between concepts. The process described can be …

Privacy-By-Design In Federated Social Web Applications, Alexandre Passant, Owen Sacco, Julia Anaya, Pavan Kapanipathi

Kno.e.sis Publications

No abstract provided.

Local Closed-World Reasoning With Description Logics Under The Well-Founded Semantics, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler

Computer Science and Engineering Faculty Publications

An important question for the upcoming Semantic Web is how to best combine open world ontology languages, such as the OWL-based ones, with closed world rule-based languages. One of the most mature proposals for this combination is known as hybrid MKNF knowledge bases (Motik and Rosati, 2010 [52]), and it is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. In this paper we propose a well-founded semantics for nondisjunctive hybrid MKNF knowledge bases that promises to provide better efficiency of reasoning, and that is compatible with both the OWL-based …

Developing Digital Field Guides For Plants: A Study From The Perspective Of Users, Emily Roseanne Schwarz

Master's Theses

A field guide is a tool to identify an object of natural history. Field guides
cover a wide range of topics from plants to fungi, birds to mammals, and shells to minerals. Traditionally, field guides are books, usually small enough to be carried outdoors . They enjoy wide popularity in modern life; almost every American home and library owns at least one field guide, and the same is also true for other areas of the world.

At this time, companies, non-profits, and universities are developing computer
technologies to replace printed field guides for identifying plants. This thesis
examines the state …

Query Weighting For Ranking Model Adaptation, Peng Cai, Wei Gao, Aoying Zhou, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

We propose to directly measure the importance of queries in the source domain to the target domain where no rank labels of documents are available, which is referred to as query weighting. Query weighting is a key step in ranking model adaptation. As the learning object of ranking algorithms is divided by query instances, we argue that it’s more reasonable to conduct importance weighting at query level than document level. We present two query weighting schemes. The first compresses the query into a query feature vector, which aggregates all document instances in the same query, and then conducts query weighting …

Regret Minimizing Audits: A Learning-Theoretic Basis For Privacy Protection, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Audit mechanisms are essential for privacy protection in permissive access control regimes, such as in hospitals where denying legitimate access requests can adversely affect patient care. Recognizing this need, we develop the first principled learning-theoretic foundation for audits. Our first contribution is a game-theoretic model that captures the interaction between the defender (e.g., hospital auditors) and the adversary (e.g., hospital employees). The model takes pragmatic considerations into account, in particular, the periodic nature of audits, a budget that constrains the number of actions that the defender can inspect, and a loss function that captures the economic impact of detected and …

Link Type Based Pre-Cluster Pair Model For Coreference Resolution, Yang Song, Houfeng Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

This paper presents our participation in the CoNLL-2011 shared task, Modeling Unrestricted Coreference in OntoNotes. Coreference resolution, as a difficult and challenging problem in NLP, has attracted a lot of attention in the research community for a long time. Its objective is to determine whether two mentions in a piece of text refer to the same entity. In our system, we implement mention detection and coreference resolution seperately. For mention detection, a simple classification based method combined with several effective features is developed. For coreference resolution, we propose a link type based pre-cluster pair model. In this model, pre-clustering of …

Towards Human-Like Social Multi-Agents With Memetic Automaton, Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Xian-Shun Chen

Research Collection School Of Computing and Information Systems

Memetics is a new science that has attracted increasing attentions in the recent decades. Beyond the formalism of simple hybrids, adaptive hybrids and memetic algorithms, the notion of memetic automaton as an adaptive entity that is self-contained and uses memes as building blocks of information is recently conceptualized in the context of computational intelligence as potential tools for effective problem-solving [1]. Taking this cue, this paper embarks a study on Memetic Multiagent system (MeM) towards human-like social agents with memetic automaton. Particularly, we introduce a potentially rich meme-inspired design and operational model, with Darwin’s theory of natural selections and Dawkins’ …

Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li

Research Collection School Of Computing and Information Systems

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.

Continuous Visible Nearest Neighbor Query Processing In Spatial Databases, Yunjun Gao, Baihua Zheng, Gencai Chen, Qing Li, Xiaofa Guo

Research Collection School Of Computing and Information Systems

In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of $${\langle p, R\rangle}$$ tuples such that $${p \in P}$$ is the nearest neighbor to every point r along the interval $${R \subseteq q}$$ as well as pis visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R due to the obstruction of …

Active Caching For Recommender Systems, Muhammad Umar Qasim

Dissertations

Web users are often overwhelmed by the amount of information available while carrying out browsing and searching tasks. Recommender systems substantially reduce the information overload by suggesting a list of similar documents that users might find interesting. However, generating these ranked lists requires an enormous amount of resources that often results in access latency. Caching frequently accessed data has been a useful technique for reducing stress on limited resources and improving response time. Traditional passive caching techniques, where the focus is on answering queries based on temporal locality or popularity, achieve a very limited performance gain. In this dissertation, we …

Getting To Know Social Media Analytics, Tin Seong Kam

Research Collection School Of Computing and Information Systems

Over the last five years, the unprecedented development and use of social mediating technologies such as blog, wiki, Facebook, and Tweeter have engendered radically new ways of working, playing, and creating meaning, leaving an indelible mark on nearly every domain imaginable. Despite the growing ubiquity of social mediating technologies, their potential has hardly been tapped. Effectively using data collected from social mediating technologies by the business community is far from trivial. This is mainly due to the general lack of awareness on Social Network Analysis (SNA) techniques and technologies among the business analysts and practitioners. This presentation aims to provide …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 5: Properties Analysis - Artist Housing Characteristics, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

Empirical Methods For Predicting Student Retention- A Summary From The Literature, Matt Bogard

Economics Faculty Publications

The vast majority of the literature related to the empirical estimation of retention models includes a discussion of the theoretical retention framework established by Bean, Braxton, Tinto, Pascarella, Terenzini and others (see Bean, 1980; Bean, 2000; Braxton, 2000; Braxton et al, 2004; Chapman and Pascarella, 1983; Pascarell and Ternzini, 1978; St. John and Cabrera, 2000; Tinto, 1975) This body of research provides a starting point for the consideration of which explanatory variables to include in any model specification, as well as identifying possible data sources. The literature separates itself into two major camps including research related to the hypothesis testing …

Efficient Schema Extraction From A Collection Of Xml Documents, Vijayeandra Parthepan

Masters Theses & Specialist Projects

The eXtensible Markup Language (XML) has become the standard format for data exchange on the Internet, providing interoperability between different business applications. Such wide use results in large volumes of heterogeneous XML data, i.e., XML documents conforming to different schemas. Although schemas are important in many business applications, they are often missing in XML documents. In this thesis, we present a suite of algorithms that are effective in extracting schema information from a large collection of XML documents. We propose using the cost of NFA simulation to compute the Minimum Length Description to rank the inferred schema. We also studied …

What's Happening In Semantic Web ... And What Fca Could Have To Do With It, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The Semantic Web is gaining momentum. Driven by over 10 years of focused project funding in the US and the EU, Semantic Web Technologies are now entering application areas in industry, academia, government, and the open Web.

The Semantic Web is based on the idea of describing the meaning - or semantics - of data on the Web using metadata - data that describes other data - in the form of ontologies, which are represented using logic-based knowledge representation languages. Central to the transfer of Semantic Web into practice is the Linked Open Data effort, which has already resulted in …