Public health information dissemination represents an interesting combination of broadcasting, sharing, and retrieving relevant health information. Social media-based public health information dissemination offers some particularly interesting characteristics, as individual users or members of the public actually carry out the actions that constitute the dissemination. These actions also may inherently provide novel evaluative information from a document computing perspective, providing information in relation to both documents and indeed the social media users or health consumers themselves. This paper discusses the novel aspects of social media-based public health information dissemination, including a comparison of its characteristics with search engine-based Web document retrieval. A preliminary analysis of a sample of public health advice tweets taken from a larger sample of over 4700 tweets sent by Australian health-related organization in February 2012 is described. Various preliminary measures are analyzed from this data to initially suggest possible characteristics of public health information dissemination and document evaluation in micro-blog-based systems based on this sample.
{"title":"Putting the public into public health information dissemination: social media and health-related web pages","authors":"R. Steele, Dan Dumbrell","doi":"10.1145/2407085.2407104","DOIUrl":"https://doi.org/10.1145/2407085.2407104","url":null,"abstract":"Public health information dissemination represents an interesting combination of broadcasting, sharing, and retrieving relevant health information. Social media-based public health information dissemination offers some particularly interesting characteristics, as individual users or members of the public actually carry out the actions that constitute the dissemination. These actions also may inherently provide novel evaluative information from a document computing perspective, providing information in relation to both documents and indeed the social media users or health consumers themselves. This paper discusses the novel aspects of social media-based public health information dissemination, including a comparison of its characteristics with search engine-based Web document retrieval. A preliminary analysis of a sample of public health advice tweets taken from a larger sample of over 4700 tweets sent by Australian health-related organization in February 2012 is described. Various preliminary measures are analyzed from this data to initially suggest possible characteristics of public health information dissemination and document evaluation in micro-blog-based systems based on this sample.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130326470","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}
G. Zuccon, B. Koopman, Anthony N. Nguyen, D. Vickers, Luke Butt
Search technologies are critical to enable clinical staff to rapidly and effectively access patient information contained in free-text medical records. Medical search is challenging as terms in the query are often general but those in relevant documents are very specific, leading to granularity mismatch. In this paper we propose to tackle granularity mismatch by exploiting subsumption relationships defined in formal medical domain knowledge resources. In symbolic reasoning, a subsumption (or 'is-a') relationship is a parent-child relationship where one concept is a subset of another concept. Subsumed concepts are included in the retrieval function. In addition, we investigate a number of initial methods for combining weights of query concepts and those of subsumed concepts. Subsumption relationships were found to provide strong indication of relevant information; their inclusion in retrieval functions yields performance improvements. This result motivates the development of formal models of relationships between medical concepts for retrieval purposes.
{"title":"Exploiting medical hierarchies for concept-based information retrieval","authors":"G. Zuccon, B. Koopman, Anthony N. Nguyen, D. Vickers, Luke Butt","doi":"10.1145/2407085.2407100","DOIUrl":"https://doi.org/10.1145/2407085.2407100","url":null,"abstract":"Search technologies are critical to enable clinical staff to rapidly and effectively access patient information contained in free-text medical records. Medical search is challenging as terms in the query are often general but those in relevant documents are very specific, leading to granularity mismatch.\u0000 In this paper we propose to tackle granularity mismatch by exploiting subsumption relationships defined in formal medical domain knowledge resources. In symbolic reasoning, a subsumption (or 'is-a') relationship is a parent-child relationship where one concept is a subset of another concept. Subsumed concepts are included in the retrieval function. In addition, we investigate a number of initial methods for combining weights of query concepts and those of subsumed concepts. Subsumption relationships were found to provide strong indication of relevant information; their inclusion in retrieval functions yields performance improvements. This result motivates the development of formal models of relationships between medical concepts for retrieval purposes.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127087368","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}
In this paper, we describe a machine-translated parallel English corpus for the NTCIR Chinese, Japanese and Korean (CJK) Wikipedia collections. This document collection is named CJK2E Wikipedia XML corpus. The corpus could be used by the information retrieval research community and knowledge sharing in Wikipedia in many ways; for example, this corpus could be used for experimentations in cross-lingual information retrieval, cross-lingual link discovery, or omni-lingual information retrieval research. Furthermore, the translated CJK articles could be used to further expand the current coverage of the English Wikipedia.
在本文中，我们描述了一个机器翻译的并行英语语料库，用于NTCIR中文，日语和韩语(CJK)维基百科集合。这个文档集合命名为CJK2E Wikipedia XML语料库。该语料库可用于维基百科的信息检索研究团体和知识共享;例如，该语料库可用于跨语言信息检索、跨语言链接发现或全语言信息检索研究的实验。此外，翻译后的CJK文章可用于进一步扩大英语维基百科的现有覆盖范围。
{"title":"An English-translated parallel corpus for the CJK Wikipedia collections","authors":"Ling-Xiang Tang, S. Geva, A. Trotman","doi":"10.1145/2407085.2407099","DOIUrl":"https://doi.org/10.1145/2407085.2407099","url":null,"abstract":"In this paper, we describe a machine-translated parallel English corpus for the NTCIR Chinese, Japanese and Korean (CJK) Wikipedia collections. This document collection is named CJK2E Wikipedia XML corpus. The corpus could be used by the information retrieval research community and knowledge sharing in Wikipedia in many ways; for example, this corpus could be used for experimentations in cross-lingual information retrieval, cross-lingual link discovery, or omni-lingual information retrieval research. Furthermore, the translated CJK articles could be used to further expand the current coverage of the English Wikipedia.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122135635","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}
Approximate pattern matching is an important computational problem with a wide variety of applications in Information Retrieval. Efficient solutions to approximate pattern matching can be applied to natural language keyword queries with spelling mistakes, OCR scanned text incorporated into indexes, language model ranking algorithms based on term proximity, or DNA databases containing sequencing errors. In this paper, we present a novel approach to constructing text indexes capable of efficiently supporting approximate search queries. Our approach relies on a new variant of the Context Bound Burrows-Wheeler Transform (k-bwt), referred to as the Variable Depth Burrows-Wheeler Transform (v-bwt). First, we describe our new algorithm, and show that it is reversible. Next, we show how to use the transform to support efficient text indexing and approximate pattern matching. Lastly, we empirically evaluate the use of the v-bwt for DNA and English text collections, and show a significant improvement in approximate search efficiency over more traditional q-gram based approximate pattern matching algorithms.
{"title":"Efficient indexing algorithms for approximate pattern matching in text","authors":"M. Petri, M. Petri, J. Culpepper","doi":"10.1145/2407085.2407087","DOIUrl":"https://doi.org/10.1145/2407085.2407087","url":null,"abstract":"Approximate pattern matching is an important computational problem with a wide variety of applications in Information Retrieval. Efficient solutions to approximate pattern matching can be applied to natural language keyword queries with spelling mistakes, OCR scanned text incorporated into indexes, language model ranking algorithms based on term proximity, or DNA databases containing sequencing errors. In this paper, we present a novel approach to constructing text indexes capable of efficiently supporting approximate search queries. Our approach relies on a new variant of the Context Bound Burrows-Wheeler Transform (k-bwt), referred to as the Variable Depth Burrows-Wheeler Transform (v-bwt). First, we describe our new algorithm, and show that it is reversible. Next, we show how to use the transform to support efficient text indexing and approximate pattern matching. Lastly, we empirically evaluate the use of the v-bwt for DNA and English text collections, and show a significant improvement in approximate search efficiency over more traditional q-gram based approximate pattern matching algorithms.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125600310","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}
We present an ontology to represent the key concepts of sustainability indicators that are increasingly being used to measure the economic, environmental and social properties of complex systems. There have been few efforts to represent multiple indicators formally, in spite of the fact that comparison of indicators and measurements across reporting contexts is a critical task. In this paper, we apply the METHONTOLOGY approach to guide the construction of two design candidates we term Generic and Specific. Of the two, the generic design is more abstract, with fewer classes and properties. Documents describing two indicator systems - the Global Reporting Initiative and the Organisation for Economic Co-operation and Development -- are used in the design of both candidate ontologies. We then evaluate both ontology designs using the ROMEO approach, to calculate their level of coverage against the seen indicators, as well as against an unseen third indicator set (the United Nations Statistics Division). We also show that use of existing structured approaches like METHONTOLOGY and ROMEO can reduce ambiguity in ontology design and evaluation for domain-level ontologies. It is concluded that where an ontology needs to be designed for both seen and unseen indicator systems, a generic and reusable design is preferable.
{"title":"An ontology derived from heterogeneous sustainability indicator set documents","authors":"L. Ghahremanloo, J. Thom, L. Magee","doi":"10.1145/2407085.2407095","DOIUrl":"https://doi.org/10.1145/2407085.2407095","url":null,"abstract":"We present an ontology to represent the key concepts of sustainability indicators that are increasingly being used to measure the economic, environmental and social properties of complex systems. There have been few efforts to represent multiple indicators formally, in spite of the fact that comparison of indicators and measurements across reporting contexts is a critical task. In this paper, we apply the METHONTOLOGY approach to guide the construction of two design candidates we term Generic and Specific. Of the two, the generic design is more abstract, with fewer classes and properties. Documents describing two indicator systems - the Global Reporting Initiative and the Organisation for Economic Co-operation and Development -- are used in the design of both candidate ontologies. We then evaluate both ontology designs using the ROMEO approach, to calculate their level of coverage against the seen indicators, as well as against an unseen third indicator set (the United Nations Statistics Division). We also show that use of existing structured approaches like METHONTOLOGY and ROMEO can reduce ambiguity in ontology design and evaluation for domain-level ontologies. It is concluded that where an ontology needs to be designed for both seen and unseen indicator systems, a generic and reusable design is preferable.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101975","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}
This paper uses standard information retrieval techniques to measure the quality of information exchange during Question Time in the Australian Federal Parliament's House of Representatives from 1998 to 2012. A search engine is used to index all answers to questions, and then runs each question as a query, recording the rank of the actual answer in the returned list of documents. Using this rank as a measure of quality, Question Time has deteriorated over the last decade. The main deterioration has been in information exchange in "Dorothy Dixer" questions. The corpus used for this study is available from the author's web page for further investigations.
{"title":"An attempt to measure the quality of questions in question time of the Australian Federal Parliament","authors":"A. Turpin","doi":"10.1145/2407085.2407098","DOIUrl":"https://doi.org/10.1145/2407085.2407098","url":null,"abstract":"This paper uses standard information retrieval techniques to measure the quality of information exchange during Question Time in the Australian Federal Parliament's House of Representatives from 1998 to 2012. A search engine is used to index all answers to questions, and then runs each question as a query, recording the rank of the actual answer in the returned list of documents. Using this rank as a measure of quality, Question Time has deteriorated over the last decade. The main deterioration has been in information exchange in \"Dorothy Dixer\" questions. The corpus used for this study is available from the author's web page for further investigations.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"311 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134117587","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}
Retrieval system effectiveness can be measured in two quite different ways: by monitoring the behavior of users and gathering data about the ease and accuracy with which they accomplish certain specified information-seeking tasks; or by using numeric effectiveness metrics to score system runs in reference to a set of relevance judgments. The former has the benefit of directly assessing the actual goal of the system, namely the user's ability to complete a search task; whereas the latter approach has the benefit of being quantitative and repeatable. Each given effectiveness metric is an attempt to bridge the gap between these two evaluation approaches, since the implicit belief supporting the use of any particular metric is that user task performance should be correlated with the numeric score provided by the metric. In this work we explore that linkage, considering a range of effectiveness metrics, and the user search behavior that each of them implies. We then examine more complex user models, as a guide to the development of new effectiveness metrics. We conclude by summarizing an experiment that we believe will help establish the strength of the linkage between models and metrics.
{"title":"Models and metrics: IR evaluation as a user process","authors":"Alistair Moffat, Falk Scholer, Paul Thomas","doi":"10.1145/2407085.2407092","DOIUrl":"https://doi.org/10.1145/2407085.2407092","url":null,"abstract":"Retrieval system effectiveness can be measured in two quite different ways: by monitoring the behavior of users and gathering data about the ease and accuracy with which they accomplish certain specified information-seeking tasks; or by using numeric effectiveness metrics to score system runs in reference to a set of relevance judgments. The former has the benefit of directly assessing the actual goal of the system, namely the user's ability to complete a search task; whereas the latter approach has the benefit of being quantitative and repeatable. Each given effectiveness metric is an attempt to bridge the gap between these two evaluation approaches, since the implicit belief supporting the use of any particular metric is that user task performance should be correlated with the numeric score provided by the metric. In this work we explore that linkage, considering a range of effectiveness metrics, and the user search behavior that each of them implies. We then examine more complex user models, as a guide to the development of new effectiveness metrics. We conclude by summarizing an experiment that we believe will help establish the strength of the linkage between models and metrics.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114986784","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}
Spam has long been identified as a problem that web search engines are required to deal with. Large collection sizes are also an increasing issue for institutions that do not have the necessary resources to process them in their entirety. In this paper we investigate the effect that withholding documents identified as spam has on the resources required to process large collections. We also investigate the resulting search effectiveness and efficiency when different amounts of spam are withheld. We find that by removing spam at indexing time we are able to decrease the index size without affecting the indexing throughput, and are able to improve search precision for some thresholds.
{"title":"Effects of spam removal on search engine efficiency and effectiveness","authors":"Matt Crane, A. Trotman","doi":"10.1145/2407085.2407086","DOIUrl":"https://doi.org/10.1145/2407085.2407086","url":null,"abstract":"Spam has long been identified as a problem that web search engines are required to deal with. Large collection sizes are also an increasing issue for institutions that do not have the necessary resources to process them in their entirety. In this paper we investigate the effect that withholding documents identified as spam has on the resources required to process large collections. We also investigate the resulting search effectiveness and efficiency when different amounts of spam are withheld. We find that by removing spam at indexing time we are able to decrease the index size without affecting the indexing throughput, and are able to improve search precision for some thresholds.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123938761","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}
Jaewon Kim, Paul Thomas, R. Sankaranarayana, Tom Gedeon
Although web search on mobile devices is common, little is known about how users read search result lists on a small screen. We used eye tracking to compare users' scanning behaviour of web search engine result pages on a small screen (hand-held devices) and a large screen (desktops or laptops). The objective was to determine whether search result pages should be designed differently for mobile devices. To compare scanning behaviour, we considered only the fixation time and scanning strategy using our new method called 'Trackback'. The results showed that on a small screen, users spend relatively more time to conduct a search than they do on a large screen, despite tending to look less far ahead beyond the link that they eventually select. They also show a stronger tendency to seek information within the top three results on a small screen than on a large screen. The reason for this tendency may be difficulties in reading and the relative location of page folds. The results clearly indicated that scanning behaviour during web search on a small screen is different from that on a large screen. Thus, research efforts should be invested in improving the presentation of search engine result pages on small screens, taking scanning behaviour into account. This will help provide a better search experience in terms of search time, accuracy of finding correct links, and user satisfaction.
{"title":"Comparing scanning behaviour in web search on small and large screens","authors":"Jaewon Kim, Paul Thomas, R. Sankaranarayana, Tom Gedeon","doi":"10.1145/2407085.2407089","DOIUrl":"https://doi.org/10.1145/2407085.2407089","url":null,"abstract":"Although web search on mobile devices is common, little is known about how users read search result lists on a small screen. We used eye tracking to compare users' scanning behaviour of web search engine result pages on a small screen (hand-held devices) and a large screen (desktops or laptops). The objective was to determine whether search result pages should be designed differently for mobile devices. To compare scanning behaviour, we considered only the fixation time and scanning strategy using our new method called 'Trackback'. The results showed that on a small screen, users spend relatively more time to conduct a search than they do on a large screen, despite tending to look less far ahead beyond the link that they eventually select. They also show a stronger tendency to seek information within the top three results on a small screen than on a large screen. The reason for this tendency may be difficulties in reading and the relative location of page folds. The results clearly indicated that scanning behaviour during web search on a small screen is different from that on a large screen. Thus, research efforts should be invested in improving the presentation of search engine result pages on small screens, taking scanning behaviour into account. This will help provide a better search experience in terms of search time, accuracy of finding correct links, and user satisfaction.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132741413","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}
Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.
面向实体的搜索已经成为现代搜索引擎的重要组成部分。它侧重于检索实体列表或关于特定实体的信息，而不是文档。在本文中，我们研究了实体相关信息的查找问题，即属性值对，它在搜索目标实体中起着重要的作用。本文提出了一种结合约简关系和判别模型的分解框架——条件随机场(Conditional Random Field, CRF)，用于从自由文本文档中自动发现实体相关的属性值对。这个分解框架允许我们定位潜在的文本片段，并以用户查询的属性-值对的形式识别隐藏的语义。实证分析表明，该分解框架能够有效地整合句法和语义特征，优于基于模式的分解方法。
{"title":"Finding additional semantic entity information for search engines","authors":"Jun Hou, R. Nayak, Jinglan Zhang","doi":"10.1145/2407085.2407101","DOIUrl":"https://doi.org/10.1145/2407085.2407101","url":null,"abstract":"Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.","PeriodicalId":402985,"journal":{"name":"Australasian Document Computing Symposium","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131878496","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}
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