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1.
Mariam Daoud Lynda-Tamine Lechani Mohand Boughanem 《Knowledge and Information Systems》2009,21(3):365-398
Most Web search engines use the content of the Web documents and their link structures to assess the relevance of the document
to the user’s query. With the growth of the information available on the web, it becomes difficult for such Web search engines
to satisfy the user information need expressed by few keywords. First, personalized information retrieval is a promising way
to resolve this problem by modeling the user profile by his general interests and then integrating it in a personalized document
ranking model. In this paper, we present a personalized search approach that involves a graph-based representation of the
user profile. The user profile refers to the user interest in a specific search session defined as a sequence of related queries.
It is built by means of score propagation that allows activating a set of semantically related concepts of reference ontology,
namely the ODP. The user profile is maintained across related search activities using a graph-based merging strategy. For the purpose of
detecting related search activities, we define a session boundary recognition mechanism based on the Kendall rank correlation measure that tracks changes in the dominant concepts held by the user profile relatively to a new submitted
query. Personalization is performed by re-ranking the search results of related queries using the user profile. Our experimental
evaluation is carried out using the HARD 2003 TREC collection and showed that our session boundary recognition mechanism based
on the Kendall measure provides a significant precision comparatively to other non-ranking based measures like the cosine and the WebJaccard similarity measures. Moreover, results proved that the graph-based search personalization is effective for improving the
search accuracy. 相似文献
2.
Berretti Stefano Del Bimbo Alberto Pala Pietro 《Multimedia Tools and Applications》2004,24(3):215-232
Searching information through the Internet often requires users to separately contact several digital libraries, use each library interface to author the query, analyze retrieval results and merge them with results returned by other libraries. Such a solution could be simplified by using a centralized server that acts as a gateway between the user and several distributed repositories: The centralized server receives the user query, forwards the user query to federated repositories—possibly translating the query in the specific format required by each repository—and fuses retrieved documents for presentation to the user. To accomplish these tasks efficiently, the centralized server should perform some major operations such as: resource selection, query transformation and data fusion.
In this paper we report on some aspects of MIND, a system for managing distributed, heterogeneous multimedia libraries (MIND, 2001, http://www.mind-project.org). In particular, this paper focusses on the issue of fusing results returned by different image repositories. The proposed approach is based on normalization of matching scores assigned to retrieved images by individual libraries. Experimental results on a prototype system show the potential of the proposed approach with respect to traditional solutions. 相似文献
3.
In this paper, we propose CYBER, a CommunitY
Based sEaRch engine, for information retrieval utilizing community feedback information in a DHT network. In CYBER, each user is associated
with a set of user profiles that capture his/her interests. Likewise, a document is associated with a set of profiles—one
for each indexed term. A document profile is updated by users who query on the term and consider the document as a relevant
answer. Thus, the profile acts as a consolidation of users feedback from the same community, and reflects their interests.
In this way, as one user finds a document to be relevant, another user in the same community issuing a similar query will
benefit from the feedback provided by the earlier user. Hence, the search quality in terms of both precision and recall is
improved. Moreover, we further improve the effectiveness of CYBER by introducing an index tuning technique. By choosing the
indexing terms more carefully, community-based relevance feedback is utilized in both building/refining indices and re-evaluating
queries. We first propose a naive scheme, CYBER+, which involves an index tuning technique based on past queries only, and
then re-evaluates queries in a separate step. We then propose a more complex scheme, CYBER+ +, which refines its index based
on both past queries and relevance feedback. As the index is built with more selective and accurate terms, the search performance
is further improved. We conduct a comprehensive experimental study and the results show the effectiveness of our schemes. 相似文献
4.
PVA: A Self-Adaptive Personal View Agent 总被引:3,自引:0,他引:3
Chien Chin Chen Meng Chang Chen Yeali Sun 《Journal of Intelligent Information Systems》2002,18(2-3):173-194
In this paper, we present PVA, an adaptive personal view information agent system for tracking, learning and managing user interests in Internet documents. PVA consists of three parts: a proxy, personal view constructor, and personal view maintainer. The proxy logs the user's activities and extracts the user's interests without user intervention. The personal view constructor mines user interests and maps them to a class hierarchy (i.e., personal view). The personal view maintainer synchronizes user interests and the personal view periodically. When user interests change, in PVA, not only the contents, but also the structure of the user profile are modified to adapt to the changes. In addition, PVA considers the aging problem of user interests. The experimental results show that modulating the structure of the user profile increases the accuracy of a personalization system. 相似文献
5.
针对当前主流web搜索引擎存在信息检索个性化效果差和信息检索的精确率低等缺点, 通过对已有方法的技术改进, 介绍了一种基于用户历史兴趣网页和历史查询词相结合的个性化查询扩展方法。当用户在搜索引擎上输入查询词时,能根据学习到的当前用户兴趣模型动态判定用户潜在兴趣和计算词间相关度,并将恰当的扩展查询词组提交给搜索引擎,从而实现不同用户输入同一查询词能返回不同检索结果的目的。实验验证了算法的有效性,检索精确率也比原方法有明显提高。 相似文献
6.
7.
Personalcasting: Tailored Broadcast News 总被引:1,自引:0,他引:1
Maybury Mark Greiff Warren Boykin Stanley Ponte Jay McHenry Chad Ferro Lisa 《User Modeling and User-Adapted Interaction》2004,14(1):119-144
Broadcast news sources and newspapers provide society with the vast majority of real-time information. Unfortunately, cost efficiencies and real-time pressures demand that producers, editors, and writers select and organize content for stereotypical audiences. In this article we illustrate how content understanding, user modeling, and tailored presentation generation promise personalcasts on demand. Specifically, we report on the design and implementation of a personalized version of a broadcast news understanding system, MITRE’s Broadcast News Navigator (BNN), that tracks and infers user content interests and media preferences. We report on the incorporation of Local Context Analysis to both expand the user’s original query to the most related terms in the corpus, as well as to allow the user to provide interactive feedback to enhance the relevance of selected newsstories. We describe an empirical study of the search for stories on ten topics from a video corpus. By personalizing both the selection of stories and the form in which they are delivered, we provide users with tailored broadcast news. This individual news personalization provides more fine-grained content tailoring than current personalized television program level recommenders and does not rely on externally provided program metadata. 相似文献
8.
We propose a (meta‐)search engine, called SnakeT (SNippet Aggregation for Knowledge ExtracTion), which queries more than 18 commodity search engines and offers two complementary views on their returned results. One is the classical flat‐ranked list, the other consists of a hierarchical organization of these results into folders created on‐the‐fly at query time and labeled with intelligible sentences that capture the themes of the results contained in them. Users can browse this hierarchy with various goals: knowledge extraction, query refinement and personalization of search results. In this novel form of personalization, the user is requested to interact with the hierarchy by selecting the folders whose labels (themes) best fit her query needs. SnakeT then personalizes on‐the‐fly the original ranked list by filtering out those results that do not belong to the selected folders. Consequently, this form of personalization is carried out by the users themselves and thus results fully adaptive, privacy preserving, scalable and non‐intrusive for the underlying search engines. We have extensively tested SnakeT and compared it against the best available Web‐snippet clustering engines. SnakeT is efficient and effective, and shows that a mutual reinforcement relationship between ranking and Web‐snippet clustering does exist. In fact, the better the ranking of the underlying search engines, the more relevant the results from which SnakeT distills the hierarchy of labeled folders, and hence the more useful this hierarchy is to the user. Vice versa, the more intelligible the folder hierarchy, the more effective the personalization offered by SnakeT on the ranking of the query results. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
9.
In this paper we demonstrate that it is possible to enrich query answering with a short data movie that gives insights to the original results of an OLAP query. Our method, implemented in an actual system, CineCubes, includes the following steps. The user submits a query over an underlying star schema. Taking this query as input, the system comes up with a set of queries complementing the information content of the original query, and executes them. For each of the query results, we execute a set of highlight extraction algorithms that identify interesting patterns and values in the data of the results. Then, the system visualizes the query results and accompanies this presentation with a text commenting on the result highlights. Moreover, via a text-to-speech conversion the system automatically produces audio for the constructed text. Each combination of visualization, text and audio practically constitutes a movie, which is wrapped as a PowerPoint presentation and returned to the user. 相似文献
10.
Nattakarn Ratprasartporn Jonathan Po Ali Cakmak Sulieman Bani-Ahmad Gultekin Ozsoyoglu 《The VLDB Journal The International Journal on Very Large Data Bases》2009,18(1):277-301
We identify two issues with searching literature digital collections within digital libraries: (a) there are no effective paper-scoring and ranking mechanisms. Without a scoring and ranking system, users are often forced
to scan a large and diverse set of publications listed as search results and potentially miss the important ones. (b) Topic
diffusion is a common problem: publications returned by a keyword-based search query often fall into multiple topic areas,
not all of which are of interest to users. This paper proposes a new literature digital collection search paradigm that effectively ranks search outputs, while controlling the diversity of keyword-based search query output
topics. Our approach is as follows. First, during pre-querying, publications are assigned into pre-specified ontology-based
contexts, and query-independent context scores are attached to papers with respect to the assigned contexts. When a query
is posed, relevant contexts are selected, search is performed within the selected contexts, context scores of publications
are revised into relevancy scores with respect to the query at hand and the context that they are in, and query outputs are
ranked within each relevant context. This way, we (1) minimize query output topic diversity, (2) reduce query output size,
(3) decrease user time spent scanning query results, and (4) increase query output ranking accuracy. Using genomics-oriented
PubMed publications as the testbed and Gene Ontology terms as contexts, our experiments indicate that the proposed context-based
search approach produces search results with up to 50% higher precision, and reduces the query output size by up to 70%. 相似文献
11.
《Journal of Web Semantics》2008,6(4):283-290
This article presents the CHIP demonstrator1 for providing personalized access to digital museum collections. It consists of three main components: Art Recommender, Tour Wizard, and Mobile Tour Guide. Based on the semantically enriched Rijksmuseum Amsterdam2 collection, we show how Semantic Web technologies can be deployed to (partially) solve three important challenges for recommender systems applied in an open Web context: (1) to deal with the complexity of various types of relationships for recommendation inferencing, where we take a content-based approach to recommend both artworks and art-history topics; (2) to cope with the typical user modeling problems, such as cold-start for first-time users, sparsity in terms of user ratings, and the efficiency of user feedback collection; and (3) to support the presentation of recommendations by combining different views like a historical timeline, museum map and faceted browser. Following a user-centered design cycle, we have performed two evaluations with users to test the effectiveness of the recommendation strategy and to compare the different ways for building an optimal user profile for efficient recommendations. The CHIP demonstrator received the Semantic Web Challenge Award (third prize) in 2007, Busan, Korea. 相似文献
12.
Stephanos Michos Efstathios Stamatatos Nikos Fakotakis 《Applied Artificial Intelligence》2013,27(7):679-703
Language barriers present a major problem in the effectiveness of resource sharing and in common access to the resources of libraries. In this paper we present the TRANSLIB system, which consists of an integration of both new and existing multilingual information tools. This system takes full advantage of some AI-based methods in order to provide multilingual access to library catalogues. Its main features include functionalities for searching in multiple languages, multilingual presentation of the query results, and localization of the user interface. TRANSLIB has currently been tested in existing medium-sized bibliographic databases. Evaluation results show a remarkable improvement in the search process and report high user friendliness and easy and low-cost maintenance and upgrade of the system. 相似文献
13.
A universal search engine is unable to provide a personal touch to a user query. To overcome the deficiency of a universal
search engine, vertical search engines are used, which return search results from a specific domain. An alternate option is
to use a personalized search system. In our endeavor to provide personalized search results, the proposed system, Exclusively
Your’s, observes a user browsing behavior and his actions. Based on the observed user behavior, it dynamically constructs
user profile which consists of some terms that are related to user's interest. The constructed profile is later used for query
expansion. The goal of research work in this paper is not to provide all the relevant results, but a few high quality personalized
search results at the top of ranked list, which in other words means high precision. We performed experiments by personalizing
Google, Yahoo, and Naver (widely used search engine in Korea). The results show that using Exclusively Your’s, a search engine
yields significant improvement. We also compared the user profile constructed by the proposed approach with other similar
personalization approaches; the results show a marginal increase in precision. 相似文献
14.
《Applied Artificial Intelligence》2013,27(8-9):715-744
This paper presents a system developed for adaptive retrieval and the filtering of documents belonging to digital libraries available on the Web. This system, called InfoWeb, is currently in operation on the ENEA (National Entity for Alternative Energy) digital library Web site reserved to the cultural heritage and environment domain. InfoWeb records the user information needs in a user model, created through a representation, which extends the traditional vector space model and takes the form of a semantic network consisting of co-occurrences between index terms. The initial user model is built on the basis of stereotypes, developed through a clustering of the collection by using specific documents as a starting point. The user's query can be expanded in an adaptive way, using the user model formulated by the user himself. The system has been tested on the entire collection comprising about 14,000 documents in HTML/text format. The results of the experiments are satisfactory both in terms of performance and in terms of the system's ability to adapt itself to the user's shifting interests. 相似文献
15.
基于分类方法的Web站点实时个性化推荐 总被引:28,自引:0,他引:28
提出一种新的基于分类方法的实时个性化推荐方法,该文首先根据用户访问事务文法生成序列访问事务集,用于得到每个用户访问的序列特性并且便于分类器进行分类,然后利用该事务集训练一个多类分类器,作者通过推荐引擎得到每个用户的当前访问序列和用户当前请求页面,然后把该序列送入分类器进行分类,以得到用户的下面一些可能访问的页面,这些推荐页面的地址被附加到用户当前请求的页面的底部由推荐引擎返回以进行推荐,在这种方法中,用户不需要注册信息,推荐不打扰用户,可以为用户提供实时个性化的服务,实验表明这种方法是成功的。 相似文献
16.
Ashish Mehta James Geller Yehoshua Perl Erich Neuhold 《The VLDB Journal The International Journal on Very Large Data Bases》1998,7(1):25-47
A path-method is used as a mechanism in object-oriented databases (OODBs) to retrieve or to update information relevant to one class that
is not stored with that class but with some other class. A path-method is a method which traverses from one class through
a chain of connections between classes and accesses information at another class. However, it is a difficult task for a casual
user or even an application programmer to write path-methods to facilitate queries. This is because it might require comprehensive
knowledge of many classes of the conceptual schema that are not directly involved in the query, and therefore may not even
be included in a user's (incomplete) view about the contents of the database. We have developed a system, called path-method generator (PMG), which generates path-methods automatically according to a user's database-manipulating requests. The PMG offers the
user one of the possible path-methods and the user verifies from his knowledge of the intended purpose of the request whether
that path-method is the desired one. If the path method is rejected, then the user can utilize his now increased knowledge
about the database to request (with additional parameters given) another offer from the PMG. The PMG is based on access weights attached to the connections between classes and precomputed access relevance between every pair of classes of the OODB. Specific rules for access weight assignment and algorithms for computing access
relevance appeared in our previous papers [MGPF92, MGPF93, MGPF96]. In this paper, we present a variety of traversal algorithms
based on access weights and precomputed access relevance. Experiments identify some of these algorithms as very successful
in generating most desired path-methods. The PMG system utilizes these successful algorithms and is thus an efficient tool
for aiding the user with the difficult task of querying and updating a large OODB.
Received July 19, 1993 / Accepted May 16, 1997 相似文献
17.
Personalization of content returned from a Web site is an important problem in general and affects e-commerce and e-services in particular. Targeting appropriate information or products to the end user can significantly change (for the better) the user experience on a Web site. One possible approach to Web personalization is to mine typical user profiles from the vast amount of historical data stored in access logs. We present a system that mines the logs to obtain profiles and uses them to automatically generate a Web page containing URLs the user might be interested in. Profiles generated are only based on the prior traversal patterns of the user on the Web site and do not involve providing any declarative information or require the user to log in. Profiles are dynamic in nature. With time, a users traversal pattern changes. To reflect changes to the personalized page generated for the user, the profiles have to be regenerated, taking into account the existing profile. Instead of creating a new profile, we incrementally add and/or remove information from a user profile, aiming to save time as well as physical memory requirements. 相似文献
18.
Mass personalization: social and interactive applications using sound-track identification 总被引:1,自引:0,他引:1
This paper describes mass personalization, a framework for combining mass media with a highly personalized Web-based experience. We introduce four applications for mass personalization: personalized content layers, ad hoc social communities, real-time popularity ratings and virtual media library services. Using the ambient audio originating from a television, the four applications are available with no more effort than simple television channel surfing. Our audio identification system does not use dedicated interactive TV hardware and does not compromise the user’s privacy. Feasibility tests of the proposed applications are provided both with controlled conversational interference and with “living-room” evaluations. 相似文献
19.
20.
Optimal closeness query in social networks requires obtaining the social datasets from each user so that he/she finds out a shortest social distance with any target user. For example, we can make friends in terms of the most similar social relationship of family background, education level and hobbies etc. Unfortunately, social data concerning user’s attributes might reveal personal sensitive information and be exploited maliciously. Considering the above privacy-revealing issues, this paper proposes a Privacy-Preserving Optimal Closeness Query (PP-OCQ) scheme, which achieves the secure optimal closeness query in a distributed manner without revealing the users’ sensitive information. We construct an equivalent cost graph where all users’ information are encrypted by his/her public key and the data are authenticated by signature. It employs the ElGamal Cryptosystem to achieve the privacy protection in social networks, and gives an optimal closeness query protocol without leaking the users’ sensitive information on homomorphic user ciphertexts. Then it follows the routing protocol, distributed Bellman-Ford shortest-paths protocol, to query the optimal closeness through the users’ message propagation in multiple iterations. The direction of propagation is controlled by some indicators so that each user performs corresponding operations based on homomorphism property and fails to obtain other user’s information due to the masking of random numbers. Our analysis and simulations show that the proposed scheme is efficient in terms of computation cost and communication overhead. 相似文献