Effective foreign word extraction for Korean information retrieval
In Korean text, foreign words, which are mostly transliterations of English words, are frequently used. Foreign words are usually very important index terms in Korean information retrieval since most of them are technical terms or names. So accurate foreign word extraction is crucial for high performance of information retrieval. However, accurate foreign word extraction is not easy because it inevitably accompanies word segmentation and most of the foreign words are unknown. In this paper, we present an effective foreign word recognition and extraction method. In order to accurately extract foreign words, we developed an effective method of word segmentation that involves unknown foreign words. Our word segmentation method effectively utilizes both unknown word information acquired through the automatic dictionary compilation and foreign word recognition information. Our HMM-based foreign word recognition method does not require large labeled examples for the model training unlike the previously proposed method.

title: Implicit ambiguity resolution using incremental clustering in cross-language information retrieval
abstract: This paper presents a method to implicitly resolve ambiguities using dynamic incremental clustering in cross-language information retrieval (CLIR) such as Korean-to-English and Japanese-to-English CLIR. The main objective of this paper shows that document clusters can effectively resolve the ambiguities tremendously increased in translated queries as well as take into account the context of all the terms in a document. In the framework we propose, a query in Korean/Japanese is first translated into English by looking up bilingual dictionaries, then documents are retrieved for the translated query terms based on the vector space retrieval model or the probabilistic retrieval model. For the top-ranked retrieved documents, query-oriented document clusters are incrementally created and the weight of each retrieved document is recalculated by using the clusters. In the experiment based on TREC CLIR test collection, our method achieved 39.41% and 36.79% improvement for translated queries without ambiguity resolution in Korean-to-English CLIR, and 17.89% and 30.46% improvements in Japanese-to-English CLIR, on the vector space retrieval and on the probabilistic retrieval, respectively. Our method achieved 12.30% improvement for all translation queries, compared with blind feedback for the probabilistic retrieval in Korean-to-English CLIR. These results indicate that cluster analysis help to resolve ambiguity.

title: A Comparison of Different Machine Transliteration Models
abstract: Machine transliteration is a method for automatically converting words in one language into phonetically equivalent ones in another language. Machine transliteration plays an important role in natural language applications such as information retrieval and machine translation, especially for handling proper nouns and technical terms. Four machine transliteration models - grapheme-based transliteration model, phoneme-based transliteration model, hybrid transliteration model, and correspondence-based transliteration model - have been proposed by several researchers. To date, however, there has been little research on a framework in which multiple transliteration models can operate simultaneously. Furthermore, there has been no comparison of the four models within the same framework and using the same data. We addressed these problems by 1) modeling the four models within the same framework, 2) comparing them under the same conditions, and 3) developing a way to improve machine transliteration through this comparison. Our comparison showed that the hybrid and correspondence-based models were the most effective and that the four models can be used in a complementary manner to improve machine transliteration performance.

title: Knowledge Seeking Activities for Content Intelligence
abstract: This paper proposes a problem on the knowledge seeking activities compared with information seeking and knowledge discovery from text. A knowledge seeking activity is accomplished by a dynamic linkage of contents that is called “content intelligence.” An algorithm called “crossover” of knowledge units is proposed.

title: Re-ranking model based on document clusters
abstract: In this paper, we describe a model of information retrieval system that is based on a document re-ranking method using document clusters. In the first step, we retrieve documents based on the inverted-file method. Next, we analyze the retrieved documents using document clusters, and re-rank them. In this step, we use static clusters and dynamic cluster view. Consequently, we can produce clusters that are tailored to characteristics of the query. We focus on the merits of the inverted-file method and cluster analysis. In other words, we retrieve documents based on the inverted-file method and analyze all terms in document based on the cluster analysis. By these two steps, we can get the retrieved results which are made by the consideration of the context of all terms in a document as well as query terms. We will show that our method achieves significant improvements over the method based on similarity search ranking alone.

title: A Korean-Japanese-Chinese Aligned Wordnet with Shared Semantic Hierarchy
abstract: A Korean-Japanese-Chinese aligned wordnet, “CoreNet” is introduced. For the purpose of this paper, the term “wordnet” refers to a network of words. It is constructed based on a shared semantic hierarchy that is originated from NTT Goidaikei (Lexical Hierarchical System). Korean wordnet was constructed through the semantic category assignment to every meaning of Korean words in a dictionary. Verbs and adjectives’ word senses are assigned to the same semantic hierarchy as that of nouns. Each sense of verbs is investigated from corpora for their usage, and compared with Japanese translation. Chinese wordnet with the same semantic hierarchy was built up based on the comparison with Korean wordnet. Each sense of Chinese verb corresponds to Korean with its argument structure. The use of the same semantic hierarchy for nouns and predicates has several advantages. First, the surface forms of nouns and predicates share the similar one, especially in Chinese words. In case of Korean and Japanese, the typical formation is like “do+Noun” in English like “Noun+suru” in Japanese and “Noun+hada” in Korean. Second, the language generation from conceptual structures takes freedom to choose the surface form whether it chooses noun phrases or verb phrases. CoreNet has been constructed by the following principles: word sense mapping to concept, corpus-based, multi-lingualism, and single concept system for multi-languages. The overall flow of construction is based on dictionary-based bootstrapping, incremental similarity-based classification and manual post-editing. Among consideration points, the followings are introduced: multiple concept mapping, verbal noun, and concept splitting. For multiple concept mapping, a word is mapped into numerous concepts that comprise respective meanings of the word. For example, school is an “institution for the instruction of students.” The word school is mapped into three concepts such as location, organization, and facility. For verbal noun, a word that is a verb is assigned to concepts after it is transformed to a noun. For example, “write” is transformed to its noun form “writing” that is mapped into a concept writing falling under event. For concept splitting, every time inconsistency among nodes of concepts is discovered, a node may be added. What differs between CoreNet and NTT Goidaikei is that CoreNet features mapping between word senses (not just words) and concepts. These works have lasted since 1994.

title: Nonrandom Clusters of Palindromes in Herpesvirus Genomes
abstract: Palindromes are symmetrical words of DNA in the sense that they read exactly the same as their reverse complementary sequences. Representing the occurrences of palindromes in a DNA molecule as points on the unit interval, the scan statistics can be used to identify regions of unusually high concentration of palindromes. These regions have been associated with the replication origins on a few herpesviruses in previous studies. However, the use of scan statistics requires the assumption that the points representing the palindromes are independently and uniformly distributed on the unit interval. In this paper, we provide a mathematical basis for this assumption by showing that in randomly generated DNA sequences, the occurrences of palindromes can be approximated by a Poisson process. An easily computable upper bound on the Wasserstein distance between the palindrome process and the Poisson process is obtained. This bound is then used as a guide to choose an optimal palindrome length in the analysis of a collection of 16 herpesvirus genomes. Regions harboring significant palindrome clusters are identified and compared to known locations of replication origins. This analysis brings out a few interesting extensions of the scan statistics that can help formulate an algorithm for more accurate prediction of replication origins.

title: A game theoretic approach to low energy wireless video streaming
abstract: This paper presents a dynamic energy management policy for a wireless video streaming system, consisting of battery-powered client and server. The paper starts from the observation that the video quality in wireless streaming is a function of three factors: encoding aptitude of the server, decoding aptitude of the client, and the wireless channel. Based on this observation, the energy consumption of a wireless video streaming system is modeled and analyzed. Using the proposed model, the optimal energy assignment to each video frame is done such that the maximum system lifetime is achieved while satisfying a given minimum video quality requirement. Experimental results show that the proposed policy increases the system lifetime by 20%.

title: Multiple Genome Alignment by Clustering Pairwise Matches
abstract: We have developed a multiple genome alignment algorithm by using a sequence clustering algorithm to combine local pairwisegenome sequence matches produced by pairwise genome alignments, e.g, BLASTZ. Sequence clustering algorithms often generate clusters of sequences such that there exists a common shared region among all sequences in each cluster. To use a sequence clustering algorithm for genome alignment, it is necessary to handle numerous local alignments between a pair of genomes. We propose a multiple genome alignment method that converts the multiple genome alignment problem to the sequence clustering problem. This method does not need to make a guide tree to determine the order of multiple alignment, and it accurately detects multiple homologous regions. As a result, our multiple genome alignment algorithm performs competitively over existing algorithms. This is shown using an experiment which compares the performance of TBA, MultiPipMaker (MPM) and our algorithm in aligning 12 groups of 56 microbial genomes and by evaluating the number of common COGs detected.

title: System level power-performance trade-offs in embedded systems using voltage and frequency scaling of off-chip buses and memory
abstract: In embedded systems, off-chip buses and memory (i.e., L2 memory as opposed to the L1 memory which is usually on-chip cache) consume significant power often more than the processor itself. In this paper for the case of an embedded system with one processor chip and one memory chip, we propose frequency and voltage scaling of the off-chip buses and the memory chip and use a known micro-architectural enhancement called a store buffer to reduce the resulting impact on execution time. Our benchmarks show a system (processor + off-chip bus + off-chip memory) power savings of 28% to 36%, an energy savings of 13% to 35%, all while increasing the execution time in the range of 1% to 29%. Previous work in power-aware computing has focused on frequency and voltage scaling of the processors or selective power-down of sub-sets of off-chip memory chips. This paper quantitatively explores voltage/frequency scaling of off-chip buses and memory as a means of trading off performance for power/energy at the system level in embedded systems.

title: PLATCOM: Current Status and Plan for the Next Stages
abstract: We have been developing a web-based system for comparing multiple genomes, PLATCOM, where users can choose genomes of their choice freely and perform analysis of the selected genomes with a suite of computational tools. PLATCOM is built on internal databases such as GenBank, COG, KEGG, and Pairwise Comparison Database (PCDB) that contains all pairwise comparisons (97,034 entries) of protein sequence files (.faa) and whole genome sequence files (.fna) of 312 replicons. Since combining multiple tools for sequence analysis requires a significant amount of programming work and knowledge on each tool, we also developed and incorporated high performance sequence data mining tools such as sequence clustering and neighborhood prediction. The next plan includes defining several data types for genome analysis and integrating system modules using data mining tools that operate on the genome data types. PLATCOM is available at http://platcom.informatics.indiana.edu.