How Query by humming, a Music Information Retrieval System, is Being Used in the Music Education Classroom

Bradshaw, Brian Korea Multimedia Society 2017 The journal of multimedia information system Vol.4 No.3

This study does a qualitative and quantitative analysis of how music by humming is being used by music educators in the classroom. Music by humming is part division of music information retrieval. In order to define what a music information retrieval system is first I need to define what it is. Berger and Lafferty (1999) define information retrieval as "someone doing a query to a retrieval system, a user begins with an information need. This need is an ideal document- perfect fit for the user, but almost certainly not present in the retrieval system's collection of documents. From this ideal document, the user selects a group of identifying terms. In the context of traditional IR, one could view this group of terms as akin to expanded query." Music Information Retrieval has its background in information systems, data mining, intelligent systems, library science, music history and music theory. Three rounds of surveys using question pro where completed. The study found that there were variances in knowledge, training and level of awareness of query by humming, music information retrieval systems. Those variance relationships where based on music specialty, level that they teach, and age of the respondents.

Search Query Expansion using Genetic Algorithm–based Clustering

Indumathi D,Chitra A,Girthana K 한국산학기술학회 2013 SmartCR Vol.3 No.1

The World Wide Web has become a resource pool for people seeking information. Current Web search engines try to deliver relevant information to users, but due to both exponential growth of information and imprecise queries, search engines cannot meet users’ information requirements. Users have to reframe queries until they get the desired information. To improve users’ search experience, some search engines provide query suggestions that are semantically related to a particular query. These systems provide the same suggestions to the same queries without considering the personal interest of the user. This paper presents an approach to provide personalized query suggestions based on a genetic algorithm?based clustering technique. This improves retrieval effectiveness and relevancy by expanding the query with additional words. Unlike existing methods, this technique provides personalized query suggestions for each individual user according to that user’s conceptual needs. The main objective of this work is to improve retrieval of information by expanding the user’s query based on the user’s domain of interest.

학술정보검색을 위한 국내 대학생의 외국어 탐색문 활용에 관한 연구

이보은,이지연 한국정보관리학회 2019 정보관리학회지 Vol.36 No.1

This study focused on understanding the Korean university students’ (both undergraduates and graduates) use of foreign language for scholarly information retrieval especially in different search strategies employed based on users’ characteristics. A new model was developed based on Ellis’s behavioral model of information seeking strategies. The research applied both quantitative and qualitative methods to analyze the data. The students used a variety of foreign language information seeking strategies at different stages of academic information retrieval based on his/her field of study or level of education. The liberal arts and social science students had more difficulty in selecting proper search terms in the foreign language than the science and technology students. This difficulty resulted in less preference for using foreign language queries by the liberal arts and social science students. The students relied more on the bibliographic and citation information in scholarly information retrieval using foreign language queries than the Korean queries. The research outcomes should provide some guidelines on how the Korean university libraries offer information literacy programs and other services based on the patrons’ characteristics. 본 연구에서는 학술정보검색에 있어 국내 대학생과 대학원생들이 외국어 탐색문을 어떻게 활용하는지, 그리고 이용자의 특성에 따라 외국어 탐색문의 활용도에 차이가 나타나는지 파악하고자 하였다. 연구 모형은 Ellis의 정보탐색과정 모형을 바탕으로 설계되었으며, 실험, 인터뷰, 통계분석 등 양적․질적인 연구방법을 모두 활용하였다. 연구 결과, 학술정보검색의 각 단계에서 국문 검색 전략과는 다른 다양한 외국어 검색 전략들이 발견되었고, 이러한 검색 전략들은 특히 이용자의 전공분야와 학력에 따라 차이를 보이는 것으로 파악되었다. 특히 인문․사회과학분야 피실험자들이 과학기술분야 피실험자들에 비해 외국어 탐색문을 선정하는 데 큰 어려움을 겪으며, 이에 따라 외국어를 활용한 검색을 선호하지 않는 점을 확인하였다. 또한 외국어 학술정보검색에서 인용정보나 발행지 정보 등 본문 이외의 정보들에 대한 의존도가 높아지는 모습을 보였다. 결과적으로 이용자의 특성에 따라 학술정보검색 과정에 외국어를 활용하는 비중이나 느끼는 어려움의 정도에 차이가 존재한다는 점을 파악할 수 있었으며, 향후 대학도서관은 이러한 이용자의 특성에 맞추어 이용자교육이나 도서관 서비스를 제공할 수 있을 것이다.

Query Subtopic Mining by Combining Multiple Semantics

Lizhen Liu,Wenbin Xu,Wei Song,HanshiWang,Chao Du 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.12

Query subtopic mining aims to find aspects to represent people’s potential intents for a query. Clustering query reformulations is the most common approach for subtopic mining these days. However, there are some challenges that the existing approaches have to face in finding both relevant and diverse subtopics, such as term mismatch and data sparseness. In this paper, a novel semantic representations for query subtopics is introduced, which including phrase embedding representation and query category distributional representation, to solve those problems mentioned above. Furthermore, we also combine multiple semantic representations into vector space model and compute a joint similarity for clustering query reformulations. To evaluate our theory an experiment is conducted on a public dataset offered by NTCIR subtopic mining project, the experimental results show that phrase embedding representation is the most effective representation while combining multiple semantics benefits short text clustering and improves the performance of query subtopic mining.

Semantic-based Query Generation For Information Retrieval

Shin Seung-Eun,Seo Young-Hoon The Korea Contents Association 2005 International Journal of Contents Vol.1 No.2

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

A Method of Chinese and Thai Cross-Lingual Query Expansion Based on Comparable Corpus

( Peili Tang ),( Jing Zhao ),( Zhengtao Yu ),( Zhuo Wang ),( Yantuan Xian ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.4

Cross-lingual query expansion is usually based on the relationship among monolingual words. Bilingual comparable corpus contains relationships among bilingual words. Therefore, this paper proposes a method based on these relationships to conduct query expansion. First, the word vectors which characterize the bilingual words are trained using Chinese and Thai bilingual comparable corpus. Then, the correlation between Chinese query words and Thai words are computed based on these word vectors, followed with selecting the Thai candidate expansion terms via the correlative value. Then, multi-group Thai query expansion sentences are built by the Thai candidate expansion words based on Chinese query sentence. Finally, we can get the optimal sentence using the Chinese and Thai query expansion method, and perform the Thai query expansion. Experiment results show that the cross-lingual query expansion method we proposed can effectively improve the accuracy of Chinese and Thai cross-language information retrieval.

A Hybrid Query Disambiguation Adaptive Approach for Web Information Retrieval

( Roliana Ibrahim ),( Shahid Kamal ),( Imran Ghani ),( Seung Ryul Jeong ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.7

In web searching, trustable and precise results are greatly affected by the inherent uncertainty in the input queries. Queries submitted to search engines are by nature ambiguous and constitute a significant proportion of the instances given to web search engines. Ambiguous queries pose real challenges for the web search engines due to versatility of information. Temporal based approaches whereas somehow reduce the uncertainty in queries but still lack to provide results according to users aspirations. Web search science has created an interest for the researchers to incorporate contextual information for resolving the uncertainty in search results. In this paper, we propose an Adaptive Disambiguation Approach (ADA) of hybrid nature that makes use of both the temporal and contextual information to improve user experience. The proposed hybrid approach presents the search results to the users based on their location and temporal information. A Java based prototype of the systems is developed and evaluated using standard dataset to determine its efficacy in terms of precision, accuracy, recall, and F1-measure. Supported by experimental results, ADA demonstrates better results along all the axes as compared to temporal based approaches.

상호정보량의 정규화에 대한 연구

이재윤 한국문헌정보학회 2003 한국문헌정보학회지 Vol.37 No.4

Mutual information, as an association measure, has been used for various purposes as well as for calculating term similarity. There are, however, some limits in mutual information. It tends to emphasize low frequency terms extremely because the marginal value of mutual information changes inversely to frequency of terms. To compensate for this limit, this study suggests relative mutual information(RMI) coefficients which normalize mutual information, and examines their characteristics in some details. The RMI coefficients also improve effectiveness of global query expansion when they are adapted to three different collections. 상호정보량은 용어간 유사도 산출을 비롯한 다양한 분야에서 연관성 척도로 사용되어왔다. 그러나 값의 범위가 일정하지 않으며 지나치게 저빈도인 경우를 선호하는 경향이 제한점으로 지적되고 있다. 이런 점을 보완하기 위해서 상호정보량을 정규화하는 상대적 상호정보량 계수를 제안하였다. 제안된 계수의 특성을 알아본 다음, 세 실험집단을 대상으로 전역적(global) 질의확장 검색을 수행한 결과 검색 성능을 향상시킬 수 있었다.

SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval

Dae Woong Jo(조대웅),Myung Ho Kim(김명호) 한국컴퓨터정보학회 2017 韓國컴퓨터情報學會論文誌 Vol.22 No.2

In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users’ search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users’ search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user’s intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.

An Efficient Density Based Ant Colony Approach on Web Document Clustering

M. Reka 한국전산응용수학회 2023 Journal of applied mathematics & informatics Vol.41 No.6

World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.