检索结果-内蒙古大学图书馆

snippet-BASED UNSUPERVISED APPROACH FOR SENTIMENT CLASSIFICATION OF CHINESE ONLINE REVIEWS

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2011年第6期10卷 1097-1110页

作者： Li, Yijun Ye, Qiang Zhang, Ziqiong Wang, Tienan Harbin Inst Technol Sch Management Harbin 150001 Peoples R China

Sentiment classification seeks to identify general attitude of a piece of text of comments or reviews on certain subject, be it positive or negative. Most existing researches on sentiment classification employ supervised learning approaches that rely on annotated data. However, sentiment is expressed differently on different subjects in different domains, and having annotated corpora for every domain of interest is not always practical. This paper proposes an unsupervised learning approach for classifying text of online reviews as recommended or not recommended. The proposed method is based on search engine snippet, summary information on the result page of a search engine. A basic assumption is that terms with similar orientation tend to co-occur. The co-occurrence is measured by utilizing snippets returned from search engines, with a query consisting of the text and a seed positive or negative word. With the information of snippets, the proposed method may estimate the association of candidate terms more accurately. This allows us to reliably predict the sentiment orientation of customer reviews. Texts of customer reviews are then classified as recommended or not recommended if the average sentiment orientations of its phrases are positive or negative. The research data set of this study consists of 600 Chinese online reviews about travel destinations retrieved from ***. Our approach achieves an accuracy of 76.5%. Factors that influence the accuracy of the sentiment classification of Chinese online reviews were discussed.

关键词： Sentiment classification unsupervised learning approach snippet online review chinese

来源：评论

学校读者我要写书评

暂无评论

snippet Generation for Semantic Web Search Engines

引用

3rd Asian Semantic Web Conference

作者： Penin, Thomas Wang, Haofen Tran, Thanh Yu, Yong Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China Univ Karlsruhe Inst AIFB Karlsruhe Germany

ISBN: (纸本)9783540897033

With the development of the Semantic Web, more and more ontologies are available for exploitation by semantic search engines. However, while semantic search engines support the retrieval of candidate ontologies, the final selection of the most appropriate ontology is still difficult for the end users. In this paper, we extend existing work on ontology summarization to support the presentation of ontology snippets. The proposed solution leverages a new semantic similarity measure to generate snippets that are based on the given query. Experimental results have shown the potential of our solution in this problem domain that is largely unexplored so far.

关键词： snippet Ontology summarization Semantic measure

来源：评论

学校读者我要写书评

暂无评论

PCSG: Pattern-Coverage snippet Generation for RDF Datasets 20th

PCSG: Pattern-Coverage Snippet Generation for RDF Datasets

引用

20th International Semantic Web Conference (ISWC)

作者： Wang, Xiaxia Cheng, Gong Lin, Tengteng Xu, Jing Pan, Jeff Z. Kharlamov, Evgeny Qu, Yuzhong Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland Robert Bosch GmbH Bosch Ctr Artificial Intelligence Gerlingen Germany Univ Oslo Dept Informat Oslo Norway

ISBN: (纸本)9783030883614;9783030883607

For reusing an RDF dataset, understanding its content is a prerequisite. To support the comprehension of its large and complex structure, existing methods mainly generate an abridged version of an RDF dataset by extracting representative data patterns as a summary. As a complement, recent attempts extract a representative subset of concrete data as a snippet. We extend this line of research by injecting the strength of summary into snippet. We propose to generate a pattern-coverage snippet that best exemplifies the patterns of entity descriptions and links in an RDF dataset. Our approach incorporates formulations of group Steiner tree and set cover problems to generate compact snippets. This extensible approach is also capable of modeling query relevance to be used with dataset search. Experiments on thousands of real RDF datasets demonstrate the effectiveness and practicability of our approach.

关键词： RDF data snippet Data pattern Dataset search

来源：评论

学校读者我要写书评

暂无评论

Generating Informative snippet to Maximize Item Visibility 13

Generating Informative Snippet to Maximize Item Visibility

引用

22nd ACM International Conference on Information and Knowledge Management (CIKM)

作者： Das, Mahashweta Rahman, Habibur Das, Gautam Hristidis, Vagelis Univ Texas Arlington Arlington TX 76019 USA Qatar Comp Res Inst Ar Rayyan Qatar Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9781450322638

The widespread use and growing popularity of online collaborative content sites has created rich resources for users to consult in order to make purchasing decisions on various items such as e-commerce products, restaurants, etc. Ideally, a user wants to quickly decide whether an item is desirable, from the list of items returned as a result of her search query. This has created new challenges for producers/manufacturers (e.g., Dell) or retailers (e.g., Amazon, eBay) of such items to compose succinct summarizations of web item descriptions, henceforth referred to as snippets, that are likely to maximize the items' visibility among users. We exploit the availability of user feedback in collaborative content sites in the form of tags to identify the most important item attributes that must be highlighted in an item snippet. We investigate the problem of finding the top-k best snippets for an item that are likely to maximize the probability that the user preference (available in the form of search query) is satisfied. Since a search query returns multiple relevant items, we also study the problem of finding the best diverse set of snippets for the items in order to maximize the probability of a user liking at least one of the top items. We develop an exact top-k algorithm for each of the problem and perform detailed experiments on synthetic and real data crawled from the web to to demonstrate the utility of our problems and effectiveness of our solutions.

关键词： collaborative tagging item attributes snippet naive bayes

来源：评论

学校读者我要写书评

暂无评论

Topic-Focused Summarization of News Events Based on Biased snippet Extraction and Selection 1

引用

10th Asia-Information-Retrieval-Societies Conference (AIRS)

作者： Lin, Pingping Xu, Shize Zhang, Yan Peking Univ Dept Machine Intelligence Beijing 100871 Peoples R China Minist Educ Key Lab Machine Percept Beijing 100871 Peoples R China

ISBN: (数字)9783319128443

ISBN: (纸本)9783319128443;9783319128436

In this paper, we propose a framework to produce topic-focused summarization of news events, based on biased snippet extraction and selection. Through our approach, a summarization only retaining information related to a predefined topic (e.g. economy or politics) can be generated for a given news event to satisfy users with specific interests. To better balance coherence and coverage of the summarization, snippets rather than sentences or paragraphs are used as textual components. Topic signature is employed in snippet extraction and selection in order to emphasize the topic-biased information. Experiments conducted on real data demonstrate a good coverage, topic-relevancy, and content coherence of the summaries generated by our approach.

关键词： Topic-focused summarization snippet Topic signature

来源：评论

学校读者我要写书评

暂无评论

Compact snippet Caching for Flash-based Search Engines 15

Compact Snippet Caching for Flash-based Search Engines

引用

38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

作者： Zhang, Rui Sun, Pengyu Tong, Jiancong Stones, Rebecca J. Wang, Gang Liu, Xiaoguang Nankai Univ Coll Comp & Control Engn Tianjin Peoples R China Nankai Univ Coll Software Tianjin Peoples R China Baidu Inc Beijing Peoples R China

ISBN: (纸本)9781450336215

In response to a user query, search engines return the top k relevant results, each of which contains a small piece of text, called a snippet, extracted from the corresponding document. Obtaining a snippet is time consuming as it requires both document retrieval (disk access) and string matching (CPU computation), so caching of snippets is used to reduce latency. With the trend of using flash-based solid state drives (SSDs) instead of hard disk drives for search engine storage, the bottleneck of snippet generation shifts from I/O to computation. We propose a simple, but effective method for exploiting this trend, which we call fragment caching: instead of caching the whole snippet, we only cache snippet metadata which describe how to retrieve the snippet from the document. While this approach increases I/O time, the cost is insignificant on SSDs. The major benefit of fragment caching is the ability to cache the same snippets (without loss of quality) while only using a fraction of the memory the traditional method requires. In our experiments, we find around 10 times less memory is required to achieve comparable snippet generation times for dynamic memory, and we consistently achieve a vastly greater hit ratio for static caching.

关键词： Cache snippet Solid State Drive

来源：评论

学校读者我要写书评

暂无评论

Censors Attack Nrc Uranium Data the Lost A-Fuel snippet Saga

引用

2017年

Censors Attack Nrc Uranium Data the Lost A-Fuel snippet Saga by Central Intelligence Agency; Central Intelligence Agency; published by

关键词： a-fuel attack censors central intelligence agency cia crest general cia records nspr rifpub snippet uranium

来源：评论

学校读者我要写书评

暂无评论

snippet-based result merging in federated search

引用

JOURNAL OF INFORMATION SCIENCE 2023年

作者： Garba, Adamu Wu, Shangli Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 212013 Peoples R China

In federated search, the central broker simultaneously forwards the search query to multiple resources. The returned results from those resources are then merged into a single ranked list. An autonomous resource in a federated search system usually does not provide scores for the retrieved documents;even if some of them do, scores from different resources are incomparable due to the heterogeneity in many aspects of those resource involved such as retrieval models and corpus statistics. Many results merging approaches have been proposed in the literature to deal with this problem. However, to the best of our knowledge, none of them has utilised snippets. This article proposes a snippet-based weighting scheme for the query terms involved. It quantifies the importance of each query term from two angles: the frequency of the term and the part in which the term occurs inside a snippet. Three parts - which are URL, title, and description - are given different weights. Experiments are conducted with the TREC 2013 FedWeb data set. The results show that the proposed methods consistently outperform several baseline models. We also find in many instances, a further small slight performance improvement is achievable by an extra measure of weighting each of the resources involved, which can be done in the phase of resource selection.

关键词： Distributed information retrieval federated search result merging term weighting scheme snippet uncooperative environment

来源：评论

学校读者我要写书评

暂无评论

Parsing the Wiki Collection and snippet Generation

Parsing the Wiki Collection and Snippet Generation

引用

作者： Chittilla, Sai Subramanyam University of Minnesota

学位级别：M.S.

Information Retrieval (IR) is a field which deals with retrieving useful information from large sets of data in response to a query. Much information in this digital age is stored in XML format, which associates a structure with a document. Though IR systems have been used for years to access documents, the field has greatly expanded with the emergence of the world wide web, which emphasizes the structure of the data. The amount of data makes the identification of various portion(s) of a document difficult; document structure helps in this task. This thesis describes a retrieval task known as snippet retrieval. A snippet is the smallest meaningful body of text which can be used to establish the relevance of the document without actually looking at the document. The work on snippet retrieval is extended from past work in focused retrieval, wherein a ranked list of focused elements is retrieved in response to the user query. The Vector Space Model provides the framework for retrieval; we use Smart for basic retrieval functions. Our system for dynamic element retrieval, Flex, enables us to identify and rank the individual elements of each hypertext document with respect to the query. We include a discussion of focusing strategies and the use of focused elements for snippet generation. Results of our top-ranked 2011 and 2012 snippet Retrieval track runs are included.

关键词： INEX Information Retrieval Smart snippet

来源：评论

学校读者我要写书评

暂无评论

Improving Search Result Clustering by Enriching snippets with Word2Vec Model 14

Improving Search Result Clustering by Enriching Snippets wit...

引用

14th Web Information Systems and Applications Conference (WISA)

作者： Yang Nan Li Yaping Liu Qing Renmin Univ China Dept Comp Sci & Technol Sch Informat Beijing Peoples R China

ISBN: (纸本)9781538648063

Search Result Clustering (SRC) is an approach to solve the problems of web search engines under user's broad or ambiguous queries and no clues to find exact information in a long returned list. SRC groups the returned list and outputs a semantic structured organization to help users to find the desired information quickly. In a general way, the search engine results consist of concise information(snippet) about matching page documents. Because the snippet is short and carries few information, the clustering performance based on traditional TF-IDF weight is very low. An effective way to solve this problem is to enrich snippets according the semantic relationship from external text corpus. In this paper, we propose a new snippet enriching approach throughout word2vec model. The vector representations of words learned by word2vec models have been shown to carry semantic meanings and are useful in various Natural Language Processing(NLP) tasks. We pro- pose to use the top-n similar words in word2vec model to enrich snippets and we still use traditional TF-IDF weights schema to select features. In order to demonstrate the effectiveness of our method, we design intensive experiments to evaluate new method and baseline methods. The result of the analysis shows that proposed method outperforms baseline approach significantly.

关键词： search result clustering snippet word embedding

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：