Personalized topic-based tag recommendation

More and more content on the Web is generated by users. To organize this information and make it accessible via current search technology, tagging systems have gained tremendous popularity. Especially for multimedia content they allow to annotate resources with keywords (tags) which opens the door for classic text-based information retrieval. To support the user in choosing the right keywords, tag recommendation algorithms have emerged. In this setting, not only the content is decisive for recommending relevant tags but also the user's preferences.In this paper we introduce an approach to personalized tag recommendation that combines a probabilistic model of tags from the resource with tags from the user. As models we investigate simple language models as well as Latent Dirichlet Allocation. Extensive experiments on a real world dataset crawled from a big tagging system show that personalization improves tag recommendation, and our approach significantly outperforms state-of-the-art approaches.     

融合主题与语言模型的个性化标签推荐方法研究

随着Web的推广和普及,产生了越来越多的网络数据。 广泛应用了 标签系统 ,以便人们使用搜索技术来组织和使用这些信息。这些数据允许用户使用关键字(标签)注释资源,为传统的基于文本的信息检索提供了方案。为了支持用户选择正确的关键字,标签推荐算法应运而生。提出了一种个性化标签推荐方法,该方法综合了用户的资源标签与标签概率模型。该模型利用了简单语言模型和隐含狄利克雷分配模型,并针对现实世界的大型数据集进行了大量实验。实验表明,该个性化方法改进了标签推荐算法,推荐结果优于传统方法。     

Supporting Creativity through the Interactive Exploratory Search Paradigm

In creative tasks, there is a need to explore the space of available information in order to come up with diverse views before converging to a solution. In such tasks, typical search engines that follow the direct search paradigm fail to inspire users. It is hypothesized that contrary to typical engines, interactive exploratory search, which aims at revealing latent, alternative directions in the information space enabling user orientation and engagement, is better suited to assist users in their quest for serendipitous discoveries and inspiration. In this study, an interactive exploratory search tool that combines diversification of content and sources with a user interface design that visualizes clues from the social chatter – generated with micro-blogging services such as Twitter – and lets users interactively explore the available information space is presented. A profiling service and recommendation module in charge of delivering personalized social content complements the setting. A pilot and two task-based user studies comparing our system to a query-based baseline indicate that our system significantly improves inspirational discoveries by providing access to more interesting and serendipitous information.     

基于内容的视频查询系统研究

由于多媒体数据库管理和检索的效率直接决定了人们利用多媒体数据信息的效率,因此随着MPEG-7标准的提出,基于内容的图象/视频存储和检索已成为研究的热点.为了快速地对视频进行浏览和检索,在研究基于内容的视频数据库管理和检索等热点问题的基础上,首先使用MPEG-7视觉内容描述子和语义描述子来构建视频数据库的语义结构,并结合底层视觉特征和高层语义特征,采用相关反馈机制和半自动权重更新体制来对视频数据库进行管理和检索;然后采用语法分析器来支持自然语言查询;最后在此基础上实现了基于内容的视频数据库的管理和查询系统.实验证明,该系统能够有效地对视频数据进行管理和检索,并且具有一定的智能性和适应性.     

A content search system considering the activity and context of a mobile user

People routinely carry mobile devices in their daily lives and obtain a variety of information from the Internet in many different situations. In searching for information (content) with a mobile device, a user’s activity (e.g., moving or stationary) and context (e.g., commuting in the morning or going downtown in the evening) often change, and such changes can affect the user’s degree of concentration on his or her mobile device’s display and information needs. Therefore, a search system should provide the user with an amount of information suitable for the current activity and a type of information suitable for the current context. In this study, we present the design and implementation of a content search system that considers a mobile user’s activity and context, with the goal of reducing the user’s operation load for content search. The proposed system switches between two kinds of content search systems according to the user’s activity: the location-based content search system is activated when the user is stationary (e.g., standing and sitting), while a menu-based content search system is activated when the user is moving (e.g., walking). Both systems present information according to user context. The location-based system presents detailed information via menus and a map according to location-based categories. The menu-based system presents only a few options to enable users to get content easily. Through user experiments, we confirmed that participants could get desired information more easily with this system than with a commercial search system.     

Multiple coordinated views for searching and navigating Web content repositories

The advantages and positive effects of multiple coordinated views on search performance have been documented in several studies. This paper describes the implementation of multiple coordinated views within the Media Watch on Climate Change, a domain-specific news aggregation portal available at www.ecoresearch.net/climate that combines a portfolio of semantic services with a visual information exploration and retrieval interface. The system builds contextualized information spaces by enriching the content repository with geospatial, semantic and temporal annotations, and by applying semi-automated ontology learning to create a controlled vocabulary for structuring the stored information. Portlets visualize the different dimensions of the contextualized information spaces, providing the user with multiple views on the latest news media coverage. Context information facilitates access to complex datasets and helps users navigate large repositories of Web documents. Currently, the system synchronizes information landscapes, domain ontologies, geographic maps, tag clouds and just-in-time information retrieval agents that suggest similar topics and nearby locations.     

RésuMatcher: A personalized résumé-job matching system

Online jobs search through popular websites are quite beneficial having served for many years as a prominent tool for job seekers and employers alike. In spite of their valuable utility in linking employers with potential employees, the search process and technology utilized by job search websites have not kept pace with the rapid changes in computing capability and machine intelligence. The Information retrieval techniques utilized by these websites rely primarily on variants of manually entered search queries with some advanced similarity metrics for ranking search results.Advancements in machine intelligence techniques have enabled programmatic extraction of pertinent information about the job seeker and job postings without active user input. To this end, we developed a resume matching system, RésuMatcher, which intelligently extracts the qualifications and experience of a job seeker directly from his/her résumé, and relevant information about the qualifications and experience requirements of job postings. Using a novel statistical similarity index, RésuMatcher returns results that are more relevant to the job seekers experience, academic, and technical qualifications, with minimal active user input.Our method provides up to a 34% improvement over existing information retrieval methods in the quality of search results. In addition however, RésuMatcher requires minimal active user input to search for jobs, compared to traditional manual search-based methods prevalent today. These improvements, we hypothesize, will lead to more relevant job search results and a better overall job search experience for job seekers.As an alternative to the fragmented organization-centric job application process, job recruitment websites offered the promise of simplifying and streamlining the job search process. However, these websites offer limited functionality using generic and simplistic information retrieval methods, which being non-domain lead to a poor and frustrating search experience. In this paper, we present RésuMatcher, a personalized job-résumé matching system, which offers a novel statistical similarity index for ranking relevance between candidate résumés and a database of available jobs. In our experiments we show that our method offers a 37.44% improvement over existing information retrieval methods in the quality of matches returned.     

一个基于视图的数据访问模型

多用户共享一个数据库必然存在一些安全隐患,须加以特定的控制措施以防止非法访问。提出一个基于视图的数据访问模型(VBAC),根据用户名创建与之联系的视图(视图成为该用户访问属于他的数据的惟一窗口),回收所有用户的权限,并将视图的访问权限授予给与之对应的用户,当一个用户登录系统,将他与对应的视图绑定起来,用户的数据访问通过视图间接完成,一旦回收视图的授权,与之对应的用户将不能对数据库进行任何存取。通过授权的数据视图,将用户对数据的操纵限定在特定的行和列,在用户和数据库之间建立信息安全防火墙。在Microsoft SQL Server 2000下测试了该模型的有效性。     

A Review of Ontology‐Based Tag Recommendation Approaches

Tag recommender schemes suggest related tags for an untagged resource and better tag suggestions to tagged resources. Tagging is very important if the user identifies the tag that is more precise to use in searching interesting blogs. There is no clear information regarding the meaning of each tag in a tagging process. An user can use various tags for the same content, and he can also use new tags for an item in a blog. When the user selects tags, the resultant metadata may comprise homonyms and synonyms. This may cause an improper relationship among items and ineffective searches for topic information. The collaborative tag recommendation allows a set of freely selected text keywords as tags assigned by users. These tags are imprecise, irrelevant, and misleading because there is no control over the tag assignment. It does not follow any formal guidelines to assist tag generation, and tags are assigned to resources based on the knowledge of the users. This causes misspelled tags, multiple tags with the same meaning, bad word encoding, and personalized words without common meaning. This problem leads to miscategorization of items, irrelevant search results, wrong prediction, and their recommendations. Tag relevancy can be judged only by a specific user. These aspects could provide new challenges and opportunities to its tag recommendation problem. This paper reviews the challenges to meet the tag recommendation problem. A brief comparison between existing works is presented, which we can identify and point out the novel research directions. The overall performance of our ontology‐based recommender systems is favorably compared to other systems in the literature.     

Development of an innovative information system: a fish identification e-key with update capabilities

A dichotomous identification key organizes fishes based on their similarities and differences, and is an essential tool in which ichthyologists, biologists, fishery biologists and others can use for accurate identification of specimens or finding information on correct names, biology and distribution of species. This research work focuses on the development and implementation of a totally new information system that is able to identify correctly fish species names. The developed system is a fully interactive fish identification e-key, which can be used in both forms; locally and remotely via the World Wide Web. This new dichotomous classification e-key provides the capability to identify any species in a compact and easy to use environment, which gives the user excellent operation capabilities and complete information about all included fish species. Moreover, the application provides the capability to search for a random fish species and to show a list which includes all the fish species that currently exist in the application's database. There is an extra attribute that makes the new system novel, and this is its expandability: the information system is fully dynamic having the capability to be extended every time a new species is identified. This attribute is innovative because, until now, there is not any fish identification e-key that gives the user the capability to insert new fish species into the application's database.     

面向用户的智能信息搜索系统的设计

文章主要介绍了一个面向用户的智能信息搜索系统的设计方法,该系统能建立一个体现Web特色的用户导图库。并在搜索网络信息时,通过匹配用户导图库,学习、分析用户使用Web的经验,从而把握用户的需求,提供一些面向用户的浏览引导信息,提高了用户获取所需信息的速度。     

基于B/S结构的纳税人信息查询系统

介绍了一个基于三层B／S结构和网络数据库技术的纳税人信息查询系统的设计与实现,该信息查询系统由一个Web浏览器作为用户界面、一个数据库服务器用作信息存储和一个连接两者的Web服务器组成。     

MAPBOT: a Web based map information retrieval system

Many types of information are geographically referenced and interactive maps provide a natural user interface to such data. However, map presentation in geographical information systems and on the Web is closed related to traditional cartography and provides a very limited interactive experience. In this paper, we present MAPBOT, an interactive Web based map information retrieval system in which Web users can easily and efficiently search geographical information with the assistance of a user interface agent (UIA). Each kind of map feature such as a building or a motorway works as an agent called a Maplet. Each Maplet has a user interface level to assist the user to find information of interest and a graphic display level that controls the presence and the appearance of the feature on the map. The semantic relationships of Maplets are defined in an Ontology Repository provided by the system which is used by the UIA to assist a user to semantically and efficiently search map information interested. An Ontology Editor with a graphic user interface has been implemented to update the Ontology Repository. Visualization on the client is based on Scalable Vector Graphics which provides a high quality Web map.     

A Relation-Based Page Rank Algorithm for Semantic Web Search Engines

With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. Next generation Web architecture, represented by Semantic Web, provides the layered architecture possibly allowing to overcome this limitation. Several search engines have been proposed, which allow to increase information retrieval accuracy by exploiting a key content of Semantic Web resources, that is relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information which could be extracted from user query and annotated resource. Relevance is measured as the probability that retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.     

User-private information retrieval based on a peer-to-peer community

Private information retrieval (PIR) is normally modeled as a game between two players: a user and a database. The user wants to retrieve some item from the database without the latter learning which item is retrieved. Most current PIR protocols are ill-suited to provide PIR from a search engine or large database: (i) their computational complexity is linear in the size of the database; (ii) they assume active cooperation by the database server in the PIR protocol. If the database cannot be assumed to cooperate, a peer-to-peer (P2P) user community is a natural alternative to achieve some query anonymity: a user gets her queries submitted on her behalf by other users in the P2P community. In this way, the database still learns which item is being retrieved, but it cannot obtain the real query histories of users, which become diffused among the peer users. We name this relaxation of PIR user-private information retrieval (UPIR). A peer-to-peer UPIR system is described in this paper which relies on an underlying combinatorial structure to reduce the required key material and increase availability. Extensive simulation results are reported and a distributed key management version of the system is described.     

A similarity-based reasoning model for intelligent interfaces

We present a reasoning model based on psychological similarity and discuss its application to database interfaces. In our approach, relationships in a relational type of database are translated to similarity relationships between data through a psychological model of similarity. The siimilarity relationships are integrated into a network-type of knowledge base. A function of information propagation in the knowledge base, based on a psychological model of stimulus generalization, is implemented in order to enable a similarity-based search through the database. Using this information propagation function, the computer also determines the generic kind of question it should next pose to the user. The user is allowed to give indefinite answers which reflect lack of knowledge or knowledge imprecision, and also to take control of the dialog when necessary. Through this dialog process, the interface system aids the user in specifying requests for relevant data, as well as in retrieving data from the database.     

基于内容的对象存储技术的研究

由于目前的内容寻址存储系统在应用时存在很大的问题,提出基于标准HTTP协议开发CAS存储接口,将文件操作映射为URI资源的标签语义,实现基于Web的文件存取和操作;并借助Web服务器和数据库建立功能强大的CAS客户端,基于元数据模型并结合数据库对文件对象进行描述,通过Web界面进行文件对象浏览和搜索,构建具有强大内容导航和搜索能力的对象存储系统.     

Query rewriting for SWIFT (First) answers

Traditionally, the answer to a database query is construed as the set of all tuples that meet the criteria stated. Strict adherence to this notion in query evaluation is, however, increasingly unsatisfactory because decision makers are more prone to adopting an exploratory strategy for information search which we call “getting some answers quickly, and perhaps more later”. From a decision-maker's perspective, such a strategy is optimal for coping with information overload and makes economic sense (when used in conjunction with a micropayment mechanism). These new requirements present new opportunities for database query optimization. In this paper, we propose a progressive query processing strategy that exploits this behavior to conserve system resources and to minimize query response time and user waiting time. This is accomplished by the heuristic decomposition of user queries into subqueries that can be evaluated on demand. To illustrate the practicality of the proposed methods, we describe the architecture of a prototype system that provides a nonintrusive implementation of our approach. Finally, we present experimental results obtained from an empirical study conducted using an Oracle server that demonstrate the benefits of the progressive query processing strategy     

Automatic tag expansion using visual similarity for photo sharing websites

In this paper we present an automatic photo tag expansion method designed for photo sharing websites. The purpose of the method is to suggest tags that are relevant to the visual content of a given photo at upload time. Both textual and visual cues are used in the process of tag expansion. When a photo is to be uploaded, the system asks for a couple of initial tags from the user. The initial tags are used to retrieve relevant photos together with their tags. These photos are assumed to be potentially content related to the uploaded target photo. The tag sets of the relevant photos are used to form the candidate tag list, and visual similarities between the target photo and relevant photos are used to give weights to these candidate tags. Tags with the highest weights are suggested to the user. The method is applied on Flickr (). Results show that including visual information in the process of photo tagging increases accuracy with respect to text-based methods.     

A hybrid system approach for supporting digital libraries

A digital library (DL) consists of a database which contains library information and a user interface which provides a visual window for users to search relevant information stored in the database. Thus, an abstract structure of a digital library can be defined as a combination of a special purpose database and a user-friendly interface. This paper addresses one of the fundamental aspects of such a combination. This is the formal data structure for linking an object oriented database with hypermedia to support digital libraries. It is important to establish a formal structure for a digital library in order to efficiently maintain different types of library information. This article discusses how to build an object oriented hybrid system to support digital libraries. In particular, we focus on the discussion of a general purpose data model for digital libraries and the design of the corresponding hypermedia interface. The significant features of this research are, first, a formalized data model to define a digital library system structure; second, a practical approach to manage the global schema of a library system; and finally, a design strategy to integrate hypermedia with databases to support a wide range of application areas. Received: 15 December 1997 / Revised: June 1999