Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320024
S. Amer-Yahia, Y. Kotidis
Business applications often exchange large amounts of enterprise data stored in legacy systems. The advent of XML as a standard specification format has improved applications interoperability. However, optimizing the performance of XML data exchange, in particular, when data volumes are large, is still in its infancy. Quite often, the target system has to undo some of the work the source did to assemble documents in order to map XML elements into its own data structures. This publish&map process is both resource and time consuming. In this paper, we develop a middle-tier Web services architecture to optimize the exchange of large XML data volumes. The key idea is to allow systems to negotiate the data exchange process using an extension to WSDL. The source (target) can specify document fragments that it is willing to produce (consume). Given these fragmentations, the middleware instruments the data exchange process between the two systems to minimize the number of necessary operations and optimize the distributed processing between the source and the target systems. We show that our new exchange paradigm outperforms publish&map and enables more flexible scenarios without necessitating substantial modifications to the underlying systems.
{"title":"A Web-services architecture for efficient XML data exchange","authors":"S. Amer-Yahia, Y. Kotidis","doi":"10.1109/ICDE.2004.1320024","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320024","url":null,"abstract":"Business applications often exchange large amounts of enterprise data stored in legacy systems. The advent of XML as a standard specification format has improved applications interoperability. However, optimizing the performance of XML data exchange, in particular, when data volumes are large, is still in its infancy. Quite often, the target system has to undo some of the work the source did to assemble documents in order to map XML elements into its own data structures. This publish&map process is both resource and time consuming. In this paper, we develop a middle-tier Web services architecture to optimize the exchange of large XML data volumes. The key idea is to allow systems to negotiate the data exchange process using an extension to WSDL. The source (target) can specify document fragments that it is willing to produce (consume). Given these fragmentations, the middleware instruments the data exchange process between the two systems to minimize the number of necessary operations and optimize the distributed processing between the source and the target systems. We show that our new exchange paradigm outperforms publish&map and enables more flexible scenarios without necessitating substantial modifications to the underlying systems.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131584361","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320067
Ilias Nitsos, Georgios Evangelidis, D. Dervos
Here we report on our implementation of a hybrid-indexing scheme (bitmap-tree) that combines the advantages of bitmap indexing and file inversion. The results we obtained are compared to those of the compressed inverted file index. Both storage overhead and query processing efficiency are taken into consideration. The proposed new method is shown to excel in handling queries involving set operations. For general-purpose user queries, the bitmap-tree is shown to perform as good as the compressed inverted file index.
{"title":"Bitmap-tree indexing for set operations on free text","authors":"Ilias Nitsos, Georgios Evangelidis, D. Dervos","doi":"10.1109/ICDE.2004.1320067","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320067","url":null,"abstract":"Here we report on our implementation of a hybrid-indexing scheme (bitmap-tree) that combines the advantages of bitmap indexing and file inversion. The results we obtained are compared to those of the compressed inverted file index. Both storage overhead and query processing efficiency are taken into consideration. The proposed new method is shown to excel in handling queries involving set operations. For general-purpose user queries, the bitmap-tree is shown to perform as good as the compressed inverted file index.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132218395","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1319988
James Caverlee, Ling Liu, David J. Buttler
We introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient mining system for discovering and extracting QA-Pagelets from the deep Web. A unique feature of THOR is its two-phase extraction framework. In the first phase, pages from a deep Web site are grouped into distinct clusters of structurally-similar pages. In the second phase, pages from each page cluster are examined through a subtree filtering algorithm that exploits the structural and content similarity at subtree level to identify the QA-Pagelets.
{"title":"Probe, cluster, and discover: focused extraction of QA-Pagelets from the deep Web","authors":"James Caverlee, Ling Liu, David J. Buttler","doi":"10.1109/ICDE.2004.1319988","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1319988","url":null,"abstract":"We introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient mining system for discovering and extracting QA-Pagelets from the deep Web. A unique feature of THOR is its two-phase extraction framework. In the first phase, pages from a deep Web site are grouped into distinct clusters of structurally-similar pages. In the second phase, pages from each page cluster are examined through a subtree filtering algorithm that exploits the structural and content similarity at subtree level to identify the QA-Pagelets.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131813972","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320016
Khuzaima S. Daudjee, K. Salem
Lazy replication is a popular technique for improving the performance and availability of database systems. Although there are concurrency control techniques, which guarantee serializability in lazy replication systems, these techniques result in undesirable transaction orderings. Since transactions may see stale data, they may be serialized in an order different from the one in which they were submitted. Strong serializability avoids such problems, but it is very costly to implement. We propose a generalized form of strong serializability that is suitable for use with lazy replication. In addition to having many of the advantages of strong serializability, it can be implemented more efficiently. We show how generalized strong serializability can be implemented in a lazy replication system, and we present the results of a simulation study that quantifies the strengths and limitations of the approach.
{"title":"Lazy database replication with ordering guarantees","authors":"Khuzaima S. Daudjee, K. Salem","doi":"10.1109/ICDE.2004.1320016","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320016","url":null,"abstract":"Lazy replication is a popular technique for improving the performance and availability of database systems. Although there are concurrency control techniques, which guarantee serializability in lazy replication systems, these techniques result in undesirable transaction orderings. Since transactions may see stale data, they may be serialized in an order different from the one in which they were submitted. Strong serializability avoids such problems, but it is very costly to implement. We propose a generalized form of strong serializability that is suitable for use with lazy replication. In addition to having many of the advantages of strong serializability, it can be implemented more efficiently. We show how generalized strong serializability can be implemented in a lazy replication system, and we present the results of a simulation study that quantifies the strengths and limitations of the approach.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130912794","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320035
Ying Feng, D. Agrawal, A. E. Abbadi, Ahmed A. Metwally
Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the representation of a data cube. We introduce range cubing as an efficient way to compute and compress the data cube without any loss of precision. A new data structure, range trie, is used to compress and identify correlation in attribute values, and compress the input dataset to effectively reduce the computational cost. The range cubing algorithm generates a compressed cube, called range cube, which partitions all cells into disjoint ranges. Each range represents a subset of cells with the same aggregation value, as a tuple which has the same number of dimensions as the input data tuples. The range cube preserves the roll-up/drill-down semantics of a data cube. Compared to H-cubing, experiments on real dataset show a running time of less than one thirtieth, still generating a range cube of less than one ninth of the space of the full cube, when both algorithms run in their preferred dimension orders. On synthetic data, range cubing demonstrates much better scalability, as well as higher adaptiveness to both data sparsity and skew.
{"title":"Range cube: efficient cube computation by exploiting data correlation","authors":"Ying Feng, D. Agrawal, A. E. Abbadi, Ahmed A. Metwally","doi":"10.1109/ICDE.2004.1320035","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320035","url":null,"abstract":"Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the representation of a data cube. We introduce range cubing as an efficient way to compute and compress the data cube without any loss of precision. A new data structure, range trie, is used to compress and identify correlation in attribute values, and compress the input dataset to effectively reduce the computational cost. The range cubing algorithm generates a compressed cube, called range cube, which partitions all cells into disjoint ranges. Each range represents a subset of cells with the same aggregation value, as a tuple which has the same number of dimensions as the input data tuples. The range cube preserves the roll-up/drill-down semantics of a data cube. Compared to H-cubing, experiments on real dataset show a running time of less than one thirtieth, still generating a range cube of less than one ninth of the space of the full cube, when both algorithms run in their preferred dimension orders. On synthetic data, range cubing demonstrates much better scalability, as well as higher adaptiveness to both data sparsity and skew.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130125345","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320078
I. Bruder, A. Zeitz, Holger Meyer, B. Hänsel, A. Heuer
The need for personal information management using distributed, user-friendly, and personalized document management systems is obvious. State of the art document management systems such as digital libraries provide support for the whole document lifecycle. To enhance such document management systems to get a personalized, distributed and user-friendly information system we present techniques for a simple import of collections, documents, and data, for generic and concrete data modeling, replication, and, personalization. These techniques were employed for the implementation of a personal conference assistant, which was used for the first time at the VLDB conference 2003 in Berlin, Germany. Our client-server architecture provides an information server with different services and different kinds of clients. These services comprise a distribution and replication service, a collection integration service, a data management unit, and, a query processing service.
{"title":"FLYINGDOC: an architecture for distributed, user-friendly, and personalized information systems","authors":"I. Bruder, A. Zeitz, Holger Meyer, B. Hänsel, A. Heuer","doi":"10.1109/ICDE.2004.1320078","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320078","url":null,"abstract":"The need for personal information management using distributed, user-friendly, and personalized document management systems is obvious. State of the art document management systems such as digital libraries provide support for the whole document lifecycle. To enhance such document management systems to get a personalized, distributed and user-friendly information system we present techniques for a simple import of collections, documents, and data, for generic and concrete data modeling, replication, and, personalization. These techniques were employed for the implementation of a personal conference assistant, which was used for the first time at the VLDB conference 2003 in Berlin, Germany. Our client-server architecture provides an information server with different services and different kinds of clients. These services comprise a distribution and replication service, a collection integration service, a data management unit, and, a query processing service.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116933605","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320020
S. Chaudhuri, A. König, Vivek R. Narasayya
The ability to monitor a database server is crucial for effective database administration. Today's commercial database systems support two basic mechanisms for monitoring: (a) obtaining a snapshot of counters to capture current state, and (b) logging events in the server to a table/file to capture history. We show that for a large class of important database administration tasks the above mechanisms are inadequate in functionality or performance. We present an infrastructure called SQLCM that enables continuous monitoring inside the database server and that has the ability to automatically take actions based on monitoring. We describe the implementation of SQLCM in Microsoft SQL Server and show how several common and important monitoring tasks can be easily specified in SQLCM. Our experimental evaluation indicates that SQLCM imposes low overhead on normal server execution end enables monitoring tasks on a production server that would be too expensive using today's monitoring mechanisms.
{"title":"SQLCM: a continuous monitoring framework for relational database engines","authors":"S. Chaudhuri, A. König, Vivek R. Narasayya","doi":"10.1109/ICDE.2004.1320020","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320020","url":null,"abstract":"The ability to monitor a database server is crucial for effective database administration. Today's commercial database systems support two basic mechanisms for monitoring: (a) obtaining a snapshot of counters to capture current state, and (b) logging events in the server to a table/file to capture history. We show that for a large class of important database administration tasks the above mechanisms are inadequate in functionality or performance. We present an infrastructure called SQLCM that enables continuous monitoring inside the database server and that has the ability to automatically take actions based on monitoring. We describe the implementation of SQLCM in Microsoft SQL Server and show how several common and important monitoring tasks can be easily specified in SQLCM. Our experimental evaluation indicates that SQLCM imposes low overhead on normal server execution end enables monitoring tasks on a production server that would be too expensive using today's monitoring mechanisms.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117069682","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320036
Denilson Barbosa, A. Mendelzon, L. Libkin, L. Mignet, M. Arenas
We discuss incremental validation of XML documents with respect to DTDs and XML schema definitions. We consider insertions and deletions of subtrees, as opposed to leaf nodes only, and we also consider the validation of ID and IDREF attributes. For arbitrary schemas, we give a worst-case n log n time and linear space algorithm, and show that it often is far superior to revalidation from scratch. We present two classes of schemas, which capture most real-life DTDs, and show that they admit a logarithmic time incremental validation algorithm that, in many cases, requires only constant auxiliary space. We then discuss an implementation of these algorithms that is independent of, and can be customized for different storage mechanisms for XML. Finally, we present extensive experimental results showing that our approach is highly efficient and scalable.
{"title":"Efficient incremental validation of XML documents","authors":"Denilson Barbosa, A. Mendelzon, L. Libkin, L. Mignet, M. Arenas","doi":"10.1109/ICDE.2004.1320036","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320036","url":null,"abstract":"We discuss incremental validation of XML documents with respect to DTDs and XML schema definitions. We consider insertions and deletions of subtrees, as opposed to leaf nodes only, and we also consider the validation of ID and IDREF attributes. For arbitrary schemas, we give a worst-case n log n time and linear space algorithm, and show that it often is far superior to revalidation from scratch. We present two classes of schemas, which capture most real-life DTDs, and show that they admit a logarithmic time incremental validation algorithm that, in many cases, requires only constant auxiliary space. We then discuss an implementation of these algorithms that is independent of, and can be customized for different storage mechanisms for XML. Finally, we present extensive experimental results showing that our approach is highly efficient and scalable.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115739248","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320029
R. Sion
This paper introduces a novel method of rights protection for categorical data through watermarking. We discover new watermark embedding channels for relational data with categorical types. We design novel watermark encoding algorithms and analyze important theoretical bounds including mark vulnerability. While fully preserving data quality requirements, our solution survives important attacks, such as subset selection and random alterations. Mark detection is fully "blind" in that it doesn't require the original data, an important characteristic especially in the case of massive data. We propose various improvements and alternative encoding methods. We perform validation experiments by watermarking the outsourced Wal-Mart sales data available at our institute. We prove (experimentally and by analysis) our solution to be extremely resilient to both alteration and data loss attacks, for example tolerating up to 80% data loss with a watermark alteration of only 25%.
{"title":"Proving ownership over categorical data","authors":"R. Sion","doi":"10.1109/ICDE.2004.1320029","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320029","url":null,"abstract":"This paper introduces a novel method of rights protection for categorical data through watermarking. We discover new watermark embedding channels for relational data with categorical types. We design novel watermark encoding algorithms and analyze important theoretical bounds including mark vulnerability. While fully preserving data quality requirements, our solution survives important attacks, such as subset selection and random alterations. Mark detection is fully \"blind\" in that it doesn't require the original data, an important characteristic especially in the case of massive data. We propose various improvements and alternative encoding methods. We perform validation experiments by watermarking the outsourced Wal-Mart sales data available at our institute. We prove (experimentally and by analysis) our solution to be extremely resilient to both alteration and data loss attacks, for example tolerating up to 80% data loss with a watermark alteration of only 25%.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125917393","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}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320041
Xiaosong Ma, M. Winslett, Johnny Norris, X. Jiao, R. Fiedler
Scientific visualization applications are very data-intensive, with high demands for I/O and data management. Developers of many visualization tools hesitate to use traditional DBMSs, due to the lack of support for these DBMSs on parallel platforms and the risk of reducing the portability of their tools and the user data. We propose the GODIVA framework, which provides simple database-like interfaces to help visualization tool developers manage their in-memory data, and I/O optimizations such as prefetching and caching to improve input performance at run time. We implemented the GODIVA interfaces in a stand-alone, portable user library, which can be used by all types of visualization codes: interactive and batch-mode, sequential and parallel. Performance results from running a visualization tool using the GODIVA library on multiple platforms show that the GODIVA framework is easy to use, alleviates developers' data management burden, and can bring substantial I/O performance improvement.
{"title":"GODIVA: lightweight data management for scientific visualization applications","authors":"Xiaosong Ma, M. Winslett, Johnny Norris, X. Jiao, R. Fiedler","doi":"10.1109/ICDE.2004.1320041","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320041","url":null,"abstract":"Scientific visualization applications are very data-intensive, with high demands for I/O and data management. Developers of many visualization tools hesitate to use traditional DBMSs, due to the lack of support for these DBMSs on parallel platforms and the risk of reducing the portability of their tools and the user data. We propose the GODIVA framework, which provides simple database-like interfaces to help visualization tool developers manage their in-memory data, and I/O optimizations such as prefetching and caching to improve input performance at run time. We implemented the GODIVA interfaces in a stand-alone, portable user library, which can be used by all types of visualization codes: interactive and batch-mode, sequential and parallel. Performance results from running a visualization tool using the GODIVA library on multiple platforms show that the GODIVA framework is easy to use, alleviates developers' data management burden, and can bring substantial I/O performance improvement.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121400512","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：