KEYS '12最新文献

Theoretical results on keyword search and related problems 关键词搜索及相关问题的理论成果

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254739

Yufei Tao

引用次数: 0

STRUCT: incorporating contextual information for English query search on relational databases STRUCT:结合上下文信息，在关系数据库上进行英语查询搜索

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254742

Rajvardhan Patil, Zhengxin Chen

{"title":"STRUCT: incorporating contextual information for English query search on relational databases","authors":"Rajvardhan Patil, Zhengxin Chen","doi":"10.1145/2254736.2254742","DOIUrl":"https://doi.org/10.1145/2254736.2254742","url":null,"abstract":"Research on keyword search in database community has achieved a lot of success, and areas of interests have been moved from keyword search in relational databases to various advanced issues such as keyword search in multimedia data and data streams. Yet, many fundamental issues on keyword search in traditional databases remain. One such issue is how to interpret users' information needs behind keywords they provided. A common approach of many prototype systems is to make such interpretation as a designer's choice (such as imposing AND or OR semantics, or a combination), leaving no choice to the users. A much more meaningful approach would be allowing users themselves to specify the required semantics through contextual information. So can we build a system which stays with the simplicity of Keyword search, yet can incorporate the contextual information provided in the user query? In this paper we introduce STRUCT to explore this idea. STRUCT takes English language queries involving intended keywords; we refer to such search as English query search. Instead of resorting on a full-fledged natural language processing, the unneeded words in the queries are discarded. Only the specific contextual information along with the keywords containing database contents will be used to construct SQL queries. The contextual information is used to interpret the meaning of the queries, including the semantics involving AND, OR and NOT. In this paper we describe the architecture of STRUCT, the procedure of English query processing (parsing), the basic idea of the grouping algorithm, SQL query construction and sample results of experiments.","PeriodicalId":170987,"journal":{"name":"KEYS '12","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115939656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

A schema-driven approach for knowledge-oriented retrieval and query formulation 面向知识的检索和查询公式的模式驱动方法

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254746

H. Azzam, Sirvan Yahyaei, Marco Bonzanini, T. Roelleke

引用次数: 7

Efficient keyword search on large tree structured datasets 大型树结构数据集的高效关键字搜索

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254749

Aggeliki Dimitriou, D. Theodoratos

引用次数: 9

iSearch: an interpretation based framework for keyword search in relational databases iSearch:关系数据库中用于关键字搜索的基于解释的框架

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254741

Zhong Zeng, Z. Bao, T. Ling, M. Lee

引用次数: 14

MALEX: a MAp-like exploration model on XML database 基于XML数据库的类地图探索模型

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254744

Yong Zeng, Z. Bao, T. Ling, Luochen Li

引用次数: 2

Integrating and querying source code of programs working on a database 集成和查询在数据库上工作的程序源代码

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254747

Carlos Garcia-Alvarado, C. Ordonez

{"title":"Integrating and querying source code of programs working on a database","authors":"Carlos Garcia-Alvarado, C. Ordonez","doi":"10.1145/2254736.2254747","DOIUrl":"https://doi.org/10.1145/2254736.2254747","url":null,"abstract":"Programs and a database's schema contain complex data and control dependencies that make modifying the schema along with multiple portions of the source code difficult to change. In this paper, we address the problem of exploring and analyzing those dependencies that exist between a program and a database's schema using keyword search techniques inside a database management system (DBMS). As a result, we present QDPC, a novel system that allows the integration and flexible querying within a DBMS of source code and a database's schema. The integration focuses on obtaining the approximate matches that exist between source files (classes, function and variable names) and the database's schema (table names and column names), and then storing them in summarization tables inside a DBMS. These summarization tables are then analyzed with SQL queries to find matches that are related to a set of keywords provided by the user. It is possible to perform additional analysis of the discovered matches by computing aggregations over the obtained matches, and to perform sophisticated analysis by computing OLAP cubes. In our experiments, we show that we obtain an efficient integration and allow complex analysis of the dependencies inside the DBMS. Furthermore, we show that searching for data dependencies and building OLAP cubes can be obtained in an efficient manner. Our system opens up the possibility of using the keyword search for software engineering applications.","PeriodicalId":170987,"journal":{"name":"KEYS '12","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126329414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Towards a high quality and web-scalable table search engine 朝着高质量和网络可扩展的表搜索引擎

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254738

Cong Yu

引用次数: 7

DBSemSXplorer: semantic-based keyword search system over relational databases for knowledge discovery DBSemSXplorer:基于语义的关系数据库关键字搜索系统，用于知识发现

KEYS '12 Pub Date : 2012-05-20 DOI: 10.1145/2254736.2254748

Sina Fakhraee, F. Fotouhi

{"title":"DBSemSXplorer: semantic-based keyword search system over relational databases for knowledge discovery","authors":"Sina Fakhraee, F. Fotouhi","doi":"10.1145/2254736.2254748","DOIUrl":"https://doi.org/10.1145/2254736.2254748","url":null,"abstract":"Keyword search over relational databases has been broadly studied in recent years. Research works have been done to address both the efficiency and the effectiveness of the keyword search over relational databases. One issue with keyword search in general is its ambiguity which can ultimately impact the effectiveness of the search in terms of the quality of the search results. This ambiguity is primarily due to the ambiguity of the contextual meaning of each term in the query (e.g. each query term can be mapped to different schema terms with the same name or their synonyms). In addition to the query ambiguity itself, the relationships between the keywords in the search results are crucial for the proper interpretation of the search results by the user and should be clearly presented in the search results.\u0000 To address these issues we have designed and implemented a prototype system DBSemSXplorer which can answer the traditional keyword search over relational databases in a more effective way with a better presentation of search results. We address the keyword search ambiguity issue by adapting some of the existing approaches for keyword mapping from the query terms to the schema terms/instances. The approaches we have adapted for term mapping capture both the syntactic similarity between the query keywords and the schema terms as well as the semantic similarity (e.g. definition of the keywords) of the two and give better mappings and ultimately more accurate results. Finally, to address the last issue of lacking clear relationships among the terms appearing in the search results, our system has leveraged semantic web technologies in order to enrich the knowledgebase and to discover the relationships between the keywords.\u0000 Our experiments show that our system is more effective than the traditional keyword search approaches by enabling the users to find the search results which are more relevant to their keyword queries.","PeriodicalId":170987,"journal":{"name":"KEYS '12","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131714910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6