Unsupervised word sense disambiguation for Korean through the acyclic weighted digraph using corpus and dictionary

Word sense disambiguation (WSD) is meant to assign the most appropriate sense to a polysemous word according to its context. We present a method for automatic WSD using only two resources: a raw text corpus and a machine-readable dictionary (MRD). The system learns the similarity matrix between word pairs from the unlabeled corpus, and it uses the vector representations of sense definitions from MRD, which are derived based on the similarity matrix. In order to disambiguate all occurrences of polysemous words in a sentence, the system separately constructs the acyclic weighted digraph (AWD) for every occurrence of polysemous words in a sentence. The AWD is structured based on consideration of the senses of context words which occur with a target word in a sentence. After building the AWD per each polysemous word, we can search the optimal path of the AWD using the Viterbi algorithm. We assign the most appropriate sense to the target word in sentences with the sense on the optimal path in the AWD. By experiments, our system shows 76.4% accuracy for the semantically ambiguous Korean words.     

Optimization of some factors affecting the performance of query expansion

This paper examines the factors affecting the performance of global query expansion based on term co-occurrence data and suggests a way to maximize the retrieval effectiveness. Major parameters to be optimized through experiments are term similarity measure and the weighting scheme of additional terms. The evaluation of four similarity measures tested in query expansion reveal that mutual information and Yule's Y, which emphasize low frequency terms, achieve better performance than cosine and Jaccard coefficients that have the reverse tendency. In the evaluation of three weighting schemes, similarity weight performs well only with short queries, whereas fixed weights of approximately 0.5 and similarity rank weights were effective with queries of any length. Furthermore, the optimal similarity rank weight achieving the best overall performance seems to be the least affected by test collections and the number of additional terms. For the efficiency of retrieval, the number of additional terms needs not exceed 70 in our test collections, but the optimal number may vary according to the characteristics of the similarity measure employed.     

中国薯蓣属根状茎组系统分类的初步研究

   本文根据我国薯蓣属(Dioscorea L．)根状茎组(Sect.  Stenophora Uline)的外部形态特征、细胞染色体数、花粉形态、植物化学成分、地理分布等的规律，证明根状茎组是该属中的一个比较原始的自然类群：1．具横走的多年生地下根状茎，其它组是一年生或多年生的块茎；2．大部分是2倍体，其它组是多倍体；3．花粉粒单沟型，外壁纹饰网纹或颗粒条纹，其它组为双沟型，外壁纹饰网纹；4．含甾体皂甙元(steroidal sapogenin)，其它组不含。   我们的研究观察证明，N．N．TepaCNMeHKO根据R.Knuth系统(1924)提出的薯蓣皂甙元在该属中无分布规律的说法是无充分依据的。   本文讨论了某些组或种的划分及系统位置：取消sect.Illigerestrum Prain et Burk.；将马    肠薯蓣(D．simulans Prain et Burk．)改属根状茎组；触丝薯蓣(D．tentaculigera Prain et Burk.)应列入顶生翅组  (Sect．shannicorea Prain et Burk．)，  并提出了盾叶薯蓣  (D. zingiberensis  Wright)和穿龙薯蓣(D．nipponica Makino)种的划分和定名的意见。     

Parsimonious translation models for information retrieval

In the KL divergence framework, the extended language modeling approach has a critical problem of estimating a query model, which is the probabilistic model that encodes the user’s information need. For query expansion in initial retrieval, the translation model had been proposed to involve term co-occurrence statistics. However, the translation model was difficult to apply, because the term co-occurrence statistics must be constructed in the offline time. Especially in a large collection, constructing such a large matrix of term co-occurrences statistics prohibitively increases time and space complexity. In addition, reliable retrieval performance cannot be guaranteed because the translation model may comprise noisy non-topical terms in documents. To resolve these problems, this paper investigates an effective method to construct co-occurrence statistics and eliminate noisy terms by employing a parsimonious translation model. The parsimonious translation model is a compact version of a translation model that can reduce the number of terms containing non-zero probabilities by eliminating non-topical terms in documents. Through experimentation on seven different test collections, we show that the query model estimated from the parsimonious translation model significantly outperforms not only the baseline language modeling, but also the non-parsimonious models.     

An empirical study of query expansion and cluster-based retrieval in language modeling approach

The term mismatch problem in information retrieval is a critical problem, and several techniques have been developed, such as query expansion, cluster-based retrieval and dimensionality reduction to resolve this issue. Of these techniques, this paper performs an empirical study on query expansion and cluster-based retrieval. We examine the effect of using parsimony in query expansion and the effect of clustering algorithms in cluster-based retrieval. In addition, query expansion and cluster-based retrieval are compared, and their combinations are evaluated in terms of retrieval performance by performing experimentations on seven test collections of NTCIR and TREC.     

Religious Development in African American Adolescents: Growth Patterns That Offer Protection

Although religiosity promotes resilient outcomes in African American (AA) adolescents, there is a lack of research that examines the protective role of religious development in the context of stressful life events (SLEs). In 1,595 AA adolescents, a cohort-sequential design was used from ages 12 to 18 to examine subtypes of religiosity, as well as distinct developmental patterns within subtypes. The protective role of religious development was also examined in the context of SLEs. The study findings indicated two subtypes of religiosity—extrinsic and intrinsic religiosity—as well as low and high developmental patterns in the identified subtypes. Furthermore, the protective influence of extrinsic and intrinsic religiosity gradually diminished from age 12 to 18 in the context of SLEs.     

An Entity Theory of Intelligence Predicts Higher Cortisol Levels When High School Grades Are Declining

Grades often decline during the high school transition, creating stress. The present research integrates the biopsychosocial model of challenge and threat with the implicit theories model to understand who shows maladaptive stress responses. A diary study measured declines in grades in the first few months of high school: salivary cortisol (N = 360 students, N = 3,045 observations) and daily stress appraisals (N = 499 students, N = 3,854 observations). Students who reported an entity theory of intelligence (i.e., the belief that intelligence is fixed) showed higher cortisol when grades were declining. Moreover, daily academic stressors showed a different lingering effect on the next day's cortisol for those with different implicit theories. Findings support a process model through which beliefs affect biological stress responses during difficult adolescent transitions.     

Closing the Gap: Fostering Successful Research‐Practice Partnerships in Counselor Education

Research‐practice partnerships offer counselor educators an opportunity to generate scholarship that can promote client welfare and create systemic change in practice and policy. The purpose of this article is to articulate strategies for building and sustaining research‐practice partnerships, as well as suggest methods for evaluating these partnerships.     

Development as education for social justice

Asia Pacific Education Review - The correlation between education and development, with time, went through many changes along with the changes of perspectives. Since both of these concepts...     

Integration of technical vocabulary into peer observation of teaching for Taiwanese elementary school English teachers’ professional learning

This study explored the integration of technical vocabulary into pre-observation conferences and its influence on English teachers’ professional learning and discussion in their post-observation conferences. The conceptual framework based on Harvey [2011. “A Sociocultural-Theory-Based Study of the Impact of Mediation During Post-observation Conferences on Language Teacher Learning.” Unpublished doctoral diss., University of South Florida] and Goe, Biggers, and Croft [2012. Linking Teacher Evaluation to Professional Development: Focusing on Improving Teaching and Learning. Denver, CO: National Comprehensive Center for Teacher Quality] was used to analyse the questionnaire, audio recordings, and documents collected in seven peer observations of teaching in Taiwan. This study has two major findings. First, English teachers regarded the technical vocabulary as stimuli for their professional learning; however, the range of technical vocabulary used during the post-observation conferences was limited. Second, three major factors affected their use of technical vocabulary. A new model was proposed in order to effectively integrate technical vocabulary into peer observations of teaching for elementary school English teachers’ professional learning.