154999
Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns
Recent systems have been developed for sentiment classification, opinion recognition, and opinion analysis (e.g., detecting polarity and strength). We pursue another aspect of opinion analysis: identifying the sources of opinions, emotions, and sentiments. We view this problem as an information extraction task and adopt a hybrid approach that combines Conditional Random Fields (Lafferty et al., 2001) and a variation of AutoSlog (Riloff, 1996a). While CRFs model source identification as a sequence tagging task, AutoSlog learns extraction patterns. Our results show that the combination of these two methods performs better than either one alone. The resulting system identifies opinion sources with 79.3% precision and 59.5% recall using a head noun matching measure, and 81.2% precision and 60.6% recall using an overlap measure.
1746806
Identifying Expressions of Opinion in Context
While traditional information extraction systems have been built to answer questions about facts, subjective information extraction systems will answer questions about feelings and opinions. A crucial step towards this goal is identifying the words and phrases that express opinions in text. Indeed, although much previous work has relied on the identification of opinion expressions for a variety of sentiment-based NLP tasks, none has focused directly on this important supporting task. Moreover, none of the proposed methods for identification of opinion expressions has been evaluated at the task that they were designed to perform. We present an approach for identifying opinion expressions that uses conditional random fields and we evaluate the approach at the expression-level using a standard sentiment corpus. Our approach achieves expression-level performance within 5% of the human interannotator agreement.
12101738
OpinionFinder: A System for Subjectivity Analysis
OpinionFinder is a system that performs subjectivity analysis, automatically identifying when opinions, sentiments, speculations, and other private states are present in text. Specifically, OpinionFinder aims to identify subjective sentences and to mark various aspects of the subjectivity in these sentences, including the source (holder) of the subjectivity and words that are included in phrases expressing positive or negative sentiments.
16379329
Genetic fuzzy discretization with adaptive intervals for classification problems
We propose a genetic fuzzy discretization method for continuous numerical attributes. Traditional discretization methods categorize the continuous attributes into a number of bins. Because they are made on crisp discretization, there exists considerable information loss. Fuzzy discretization allows overlapping intervals and reflects linguistic classification. However, the number of intervals, the boundaries of intervals, and the degrees of overlapping are intractable to get optimized. We use a genetic algorithm to optimize these parameters. Experimental results showed considerable improvement on the classification accuracy over a crisp discretization and a typical fuzzy discretization.
14946468
Address assignment in DSP code generation - an integrated approach
One of the important issues in embedded system design is to optimize program code for the microprocessor to be stored in ROM. In this paper, we propose an integrated approach to the DSP address-code generation problem for minimizing the number of addressing instructions. Unlike previous works, in which code scheduling and offset assignment are performed sequentially without any interaction between them, our work tightly couples offset assignment problem with code scheduling to exploit scheduling on minimizing addressing instructions more effectively. We accomplish this by developing a fast but accurate two-phase assignment procedure which, for a sequence of code schedules, finds a sequence of memory layouts with minimum addressing instructions. Experimental results with benchmark DSP programs show improvements an average of 5.8% in the whole code size over the existing methods.
325419
Textual compression by collapsible tries
Summary form only given. In this paper, various lossless and lossy adaptations and extensions of that paradigm are developed and tested, for the most part susceptible to simple linear time implementation. This is in contrast to the existing lossy variants of the Ziv-Lempel family of encoders, which have been traditionally built around the iterated quest for the best match within an assigned fidelity, thereby resulting in algorithms that are inherently superlinear and not easy to implement and analyze. Whereas a thorough analytical treatment of the proposed method seems hard, the basic algorithm and its main variants show good performance and latitude of practical applicability
14917866
Protected heap sharing for memory-constrained java environments
Multitasking is one of capabilities we often want to have in memory-constrained embedded systems. To support multiple address spaces within a small physical memory, a simple memory management frequently encounters the lack of available memory. Our paper presents an efficient heap memory management scheme that reduces memory footprints by adaptively sharing heaps among multiple tasks in JVM environments. We modified KVM from Sun Microsystems so that Java applications acquire or release heaps in a shared pool on an as-needed basis. To protect address spaces among tasks in the absence of virtual memory capabilities, we use memory protection units (MPUs) by incorporating them into our heap sharing scheme. Our experiments with J2ME MIDP applications show significant reductions by 33% on average, ranging from 6% to 50% in memory usage over the execution. The overheads of our scheme in garbage collection are kept low. The execution times in our scheme increase only by 0.2% on average.
5197608
Address assignment combined with scheduling in DSP code generation
One of the important issues in embedded system design is to optimize program code for the microprocessor to be stored in ROM. In this paper, we propose an integrated approach to the DSP address code generation problem for minimizing the number of addressing instructions. Unlike previous works in which code scheduling and offset assignment are performed sequentially without any interaction between them, our work tightly couples offset assignment problem with code scheduling to exploit scheduling on minimizing addressing instructions more effectively. We accomplish this by developing a fast but accurate two-phase procedure which, for a sequence of code schedules, finds a sequence of memory layouts with minimum addressing instructions. Experimental results with benchmark DSP programs show improvements of 13%--33% in the address code size over Solve-SOA/GOA [7].