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1.
Caching is a crucial performance component of large-scale web search engines, as it greatly helps reducing average query response times and query processing workloads on backend search clusters. In this paper, we describe a multi-level static cache architecture that stores five different item types: query results, precomputed scores, posting lists, precomputed intersections of posting lists, and documents. Moreover, we propose a greedy heuristic to prioritize items for caching, based on gains computed by using items’ past access frequencies, estimated computational costs, and storage overheads. This heuristic takes into account the inter-dependency between individual items when making its caching decisions, i.e., after a particular item is cached, gains of all items that are affected by this decision are updated. Our simulations under realistic assumptions reveal that the proposed heuristic performs better than dividing the entire cache space among particular item types at fixed proportions.  相似文献   

2.
In the web environment, most of the queries issued by users are implicit by nature. Inferring the different temporal intents of this type of query enhances the overall temporal part of the web search results. Previous works tackling this problem usually focused on news queries, where the retrieval of the most recent results related to the query are usually sufficient to meet the user's information needs. However, few works have studied the importance of time in queries such as “Philip Seymour Hoffman” where the results may require no recency at all. In this work, we focus on this type of queries named “time-sensitive queries” where the results are preferably from a diversified time span, not necessarily the most recent one. Unlike related work, we follow a content-based approach to identify the most important time periods of the query and integrate time into a re-ranking model to boost the retrieval of documents whose contents match the query time period. For that purpose, we define a linear combination of topical and temporal scores, which reflects the relevance of any web document both in the topical and temporal dimensions, thus contributing to improve the effectiveness of the ranked results across different types of queries. Our approach relies on a novel temporal similarity measure that is capable of determining the most important dates for a query, while filtering out the non-relevant ones. Through extensive experimental evaluation over web corpora, we show that our model offers promising results compared to baseline approaches. As a result of our investigation, we publicly provide a set of web services and a web search interface so that the system can be graphically explored by the research community.  相似文献   

3.
Although most of the queries submitted to search engines are composed of a few keywords and have a length that ranges from three to six words, more than 15% of the total volume of the queries are verbose, introduce ambiguity and cause topic drifts. We consider verbosity a different property of queries from length since a verbose query is not necessarily long, it might be succinct and a short query might be verbose. This paper proposes a methodology to automatically detect verbose queries and conditionally modify queries. The methodology proposed in this paper exploits state-of-the-art classification algorithms, combines concepts from a large linguistic database and uses a topic gisting algorithm we designed for verbose query modification purposes. Our experimental results have been obtained using the TREC Robust track collection, thirty topics classified by difficulty degree, four queries per topic classified by verbosity and length, and human assessment of query verbosity. Our results suggest that the methodology for query modification conditioned to query verbosity detection and topic gisting is significantly effective and that query modification should be refined when topic difficulty and query verbosity are considered since these two properties interact and query verbosity is not straightforwardly related to query length.  相似文献   

4.
Large-scale web search engines are composed of multiple data centers that are geographically distant to each other. Typically, a user query is processed in a data center that is geographically close to the origin of the query, over a replica of the entire web index. Compared to a centralized, single-center search engine, this architecture offers lower query response times as the network latencies between the users and data centers are reduced. However, it does not scale well with increasing index sizes and query traffic volumes because queries are evaluated on the entire web index, which has to be replicated and maintained in all data centers. As a remedy to this scalability problem, we propose a document replication framework in which documents are selectively replicated on data centers based on regional user interests. Within this framework, we propose three different document replication strategies, each optimizing a different objective: reducing the potential search quality loss, the average query response time, or the total query workload of the search system. For all three strategies, we consider two alternative types of capacity constraints on index sizes of data centers. Moreover, we investigate the performance impact of query forwarding and result caching. We evaluate our strategies via detailed simulations, using a large query log and a document collection obtained from the Yahoo! web search engine.  相似文献   

5.
Query auto completion (QAC) models recommend possible queries to web search users when they start typing a query prefix. Most of today’s QAC models rank candidate queries by popularity (i.e., frequency), and in doing so they tend to follow a strict query matching policy when counting the queries. That is, they ignore the contributions from so-called homologous queries, queries with the same terms but ordered differently or queries that expand the original query. Importantly, homologous queries often express a remarkably similar search intent. Moreover, today’s QAC approaches often ignore semantically related terms. We argue that users are prone to combine semantically related terms when generating queries.We propose a learning to rank-based QAC approach, where, for the first time, features derived from homologous queries and semantically related terms are introduced. In particular, we consider: (i) the observed and predicted popularity of homologous queries for a query candidate; and (ii) the semantic relatedness of pairs of terms inside a query and pairs of queries inside a session. We quantify the improvement of the proposed new features using two large-scale real-world query logs and show that the mean reciprocal rank and the success rate can be improved by up to 9% over state-of-the-art QAC models.  相似文献   

6.
Query response times within a fraction of a second in Web search engines are feasible due to the use of indexing and caching techniques, which are devised for large text collections partitioned and replicated into a set of distributed-memory processors. This paper proposes an alternative query processing method for this setting, which is based on a combination of self-indexed compressed text and posting lists caching. We show that a text self-index (i.e., an index that compresses the text and is able to extract arbitrary parts of it) can be competitive with an inverted index if we consider the whole query process, which includes index decompression, ranking and snippet extraction time. The advantage is that within the space of the compressed document collection, one can carry out the posting lists generation, document ranking and snippet extraction. This significantly reduces the total number of processors involved in the solution of queries. Alternatively, for the same amount of hardware, the performance of the proposed strategy is better than that of the classical approach based on treating inverted indexes and corresponding documents as two separate entities in terms of processors and memory space.  相似文献   

7.
With the continuous growth in the amount of data generated in the edge-cloud environment, security risks in traditional centralized data management platforms have been concerned. Blockchain technology can be applied to guarantee safety and information transparency in data caching and trading processes. Therefore, a blockchain-based secure cost-aware data caching scheme is proposed to optimize the placement and prevent the tampering of cache data. In this scheme, under the constraints of transmission cost, edge cache size, a quantum particle swarm optimization (QPSO) algorithm is used to solve the data cache placement problem with the greatest content caching gain. A blockchain-based secure decentralized data trading model is proposed to solve the trust problem among the buyers, sellers, and agent nodes and increase incentives for users to trade data. A double auction mechanism is used to maximize social welfare. The experimental results reveal that the proposed data caching and trading scheme can reduce the data transmission cost, improve the cache hit ratio, and maximize social welfare.  相似文献   

8.
给出了在一个面向Agent、本体和关系的常识知识库中如何实现常识知识查询的过程。在查询过程中,用自然语言形式描述的查询先被转化成一种我们所定义的面向Agent和本体的描述性查询语言。接着,描述性查询被翻译成SQL查询语句。用SQL查询语句对已转化成为关系形式的常识知识库进行查询后,自然语言生成算法把以关系表为形式的查询结果转化成自然语言。实验表明,新的查询方法在查询时间上优于原有的直接在agent和本体上查询知识的旧方法。实验数据表明,查询时间缩短了大约80 %。  相似文献   

9.
A user’s single session with a Web search engine or information retrieval (IR) system may consist of seeking information on single or multiple topics, and switch between tasks or multitasking information behavior. Most Web search sessions consist of two queries of approximately two words. However, some Web search sessions consist of three or more queries. We present findings from two studies. First, a study of two-query search sessions on the AltaVista Web search engine, and second, a study of three or more query search sessions on the AltaVista Web search engine. We examine the degree of multitasking search and information task switching during these two sets of AltaVista Web search sessions. A sample of two-query and three or more query sessions were filtered from AltaVista transaction logs from 2002 and qualitatively analyzed. Sessions ranged in duration from less than a minute to a few hours. Findings include: (1) 81% of two-query sessions included multiple topics, (2) 91.3% of three or more query sessions included multiple topics, (3) there are a broad variety of topics in multitasking search sessions, and (4) three or more query sessions sometimes contained frequent topic changes. Multitasking is found to be a growing element in Web searching. This paper proposes an approach to interactive information retrieval (IR) contextually within a multitasking framework. The implications of our findings for Web design and further research are discussed.  相似文献   

10.
The structure of a retrospective information retrieval system that uses equifrequent word or text fragments is described, and its advantages over word oriented systems are mentioned briefly. Word fragments are proposed as retrieval elements, and a discussion is given of the changes required in order to process a query. Some necessary modifications in the treatment of logical operators are described, and two conditions are postulated as necessary for the successful operation of the system. Aspects of query processing are illustrated by experimental results obtained from single and two-term queries applied to a portion of the MARC tapes.  相似文献   

11.
Real time search is an increasingly important area of information seeking on the Web. In this research, we analyze 1,005,296 user interactions with a real time search engine over a 190 day period. Using query log analysis, we investigate searching behavior, categorize search topics, and measure the economic value of this real time search stream. We examine aggregate usage of the search engine, including number of users, queries, and terms. We then classify queries into subject categories using the Google Directory topical hierarchy. We next estimate the economic value of the real time search traffic using the Google AdWords keyword advertising platform. Results shows that 30% of the queries were unique (used only once in the entire dataset), which is low compared to traditional Web searching. Also, 60% of the search traffic comes from the search engine’s application program interface, indicating that real time search is heavily leveraged by other applications. There are many repeated queries over time via these application program interfaces, perhaps indicating both long term interest in a topic and the polling nature of real time queries. Concerning search topics, the most used terms dealt with technology, entertainment, and politics, reflecting both the temporal nature of the queries and, perhaps, an early adopter user-based. However, 36% of the queries indicate some geographical affinity, pointing to a location-based aspect to real time search. In terms of economic value, we calculate this real time search stream to be worth approximately US $33,000,000 (US $33 M) on the online advertising market at the time of the study. We discuss the implications for search engines and content providers as real time content increasingly enters the main stream as an information source.  相似文献   

12.
在对P2P用户行为进行分析的基础上,提出了一种自动机制,能够区分出用户对不同主题领域的关注度,计算出邻居节点查询各关注主题领域相关文档的能力,通过选择对特定领域查询能力最强的k个邻居节点转发查询消息提高效率,该机制能够区分出用户的典型行为和即兴行为,通过采用不同策略进一步提高即兴查询的效率。  相似文献   

13.
Extensible Markup Language (XML) documents are associated with time in two ways: (1) XML documents evolve over time and (2) XML documents contain temporal information. The efficient management of the temporal and multi-versioned XML documents requires optimized use of storage and efficient processing of complex historical queries. This paper provides a comparative analysis of the various schemes available to efficiently store and query the temporal and multi-versioned XML documents based on temporal, change management, versioning, and querying support. Firstly, the paper studies the multi-versioning control schemes to detect, manage, and query change in dynamic XML documents. Secondly, it describes the storage structures used to efficiently store and retrieve XML documents. Thirdly, it provides a comparative analysis of the various commercial tools based on change management, versioning, collaborative editing, and validation support. Finally, the paper presents some future research and development directions for the multi-versioned XML documents.  相似文献   

14.
Web searchers commonly have difficulties crafting queries to fulfill their information needs; even after they are able to craft a query, they often find it challenging to evaluate the results of their Web searches. Sources of these problems include the lack of support for constructing and refining queries, and the static nature of the list-based representations of Web search results. WordBars has been developed to assist users in their Web search and exploration tasks. This system provides a visual representation of the frequencies of the terms found in the first 100 document surrogates returned from an initial query, in the form of a histogram. Exploration of the search results is supported through term selection in the histogram, resulting in a re-sorting of the search results based on the use of the selected terms in the document surrogates. Terms from the histogram can be easily added or removed from the query, generating a new set of search results. Examples illustrate how WordBars can provide valuable support for query refinement and search results exploration, both when vague and specific initial queries are provided. User evaluations with both expert and intermediate Web searchers illustrate the benefits of the interactive exploration features of WordBars in terms of effectiveness as well as subjective measures. Although differences were found in the demographics of these two user groups, both were able to benefit from the features of WordBars.  相似文献   

15.
A study to compare the cost effectiveness of retrospective manual and on-line bibliographic searching is described. Forty search queries were processed against seven abstracting-indexing publications and the corresponding SDC/ORBIT data bases. Equivalent periods of coverage and searcher skill levels were used for both search models. Separate task times were measured for question analysis, searching, photocopying, shelving, and output distribution. Component costs were calculated for labor, information, reproduction, equipment, physical space, and telecommunications. Results indicate that on-line searching is generally faster, less costly, and more effective than manual searching. However, for certain query/information-source combinations, manual searching may offer some advantages in precision and turn-around time. The results of a number of related studies are reviewed.  相似文献   

16.
Social content systems contain enormous collections of unstructured user-generated content, annotated by the collaborative effort of regular Internet users. Tag-clouds have become popular interfaces that allow users to query the database of these systems by clicking relevant terms. However, these single click queries are often not expressive enough to effectively retrieve the desired content. Users have to use multiple clicks or type longer queries to satisfy their information need.  相似文献   

17.
Web queries in question format are becoming a common element of a user's interaction with Web search engines. Web search services such as Ask Jeeves – a publicly accessible question and answer (Q&A) search engine – request users to enter question format queries. This paper provides results from a study examining queries in question format submitted to two different Web search engines – Ask Jeeves that explicitly encourages queries in question format and the Excite search service that does not explicitly encourage queries in question format. We identify the characteristics of queries in question format in two different data sets: (1) 30,000 Ask Jeeves queries and 15,575 Excite queries, including the nature, length, and structure of queries in question format. Findings include: (1) 50% of Ask Jeeves queries and less than 1% of Excite were in question format, (2) most users entered only one query in question format with little query reformulation, (3) limited range of formats for queries in question format – mainly “where”, “what”, or “how” questions, (4) most common question query format was “Where can I find………” for general information on a topic, and (5) non-question queries may be in request format. Overall, four types of user Web queries were identified: keyword, Boolean, question, and request. These findings provide an initial mapping of the structure and content of queries in question and request format. Implications for Web search services are discussed.  相似文献   

18.
We will explore various ways to apply query structuring in cross-language information retrieval. In the first test, English queries were translated into Finnish using an electronic dictionary, and were run in a Finnish newspaper database of 55,000 articles. Queries were structured by combining the Finnish translation equivalents of the same English query key using the syn-operator of the InQuery retrieval system. Structured queries performed markedly better than unstructured queries. Second, the effects of compound-based structuring using a proximity operator for the translation equivalents of query language compound components were tested. The method was not useful in syn-based queries but resulted in decrease in retrieval effectiveness. Proper names are often non-identical spelling variants in different languages. This allows n-gram based translation of names not included in a dictionary. In the third test, a query structuring method where the Boolean and-operator was used to assign more weight to keys translated through n-gram matching gave good results.  相似文献   

19.
Recreational queries from users searching for places to go and things to do or see are very common in web and mobile search. Users specify constraints for what they are looking for, like suitability for kids, romantic ambiance or budget. Queries like “restaurants in New York City” are currently served by static local results or the thumbnail carousel. More complex queries like “things to do in San Francisco with kids” or “romantic places to eat in Seattle” require the user to click on every element of the search engine result page to read articles from Yelp, TripAdvisor, or WikiTravel to satisfy their needs. Location data, which is an essential part of web search, is even more prevalent with location-based social networks and offers new opportunities for many ways of satisfying information seeking scenarios.In this paper, we address the problem of recreational queries in information retrieval and propose a solution that combines search query logs with LBSNs data to match user needs and possible options. At the core of our solution is a framework that combines social, geographical, and temporal information for a relevance model centered around the use of semantic annotations on Points of Interest with the goal of addressing these recreational queries. A central part of the framework is a taxonomy derived from behavioral data that drives the modeling and user experience. We also describe in detail the complexity of assessing and evaluating Point of Interest data, a topic that is usually not covered in related work, and propose task design alternatives that work well.We demonstrate the feasibility and scalability of our methods using a data set of 1B check-ins and a large sample of queries from the real-world. Finally, we describe the integration of our techniques in a commercial search engine.  相似文献   

20.
XML has become a universal standard for information exchange over the Web due to features such as simple syntax and extensibility. Processing queries over these documents has been the focus of several research groups. In fact, there is broad literature in efficient XML query processing which explore indexes, fragmentation techniques, etc. However, for answering complex queries, existing approaches mainly analyze information that is explicitly defined in the XML document. A few work investigate the use of Prolog to increase the query possibilities, allowing inference over the data content. This can cause a significant increase in the query possibilities and expressive power, allowing access to non-obvious information. However, this requires translating the XML documents into Prolog facts. But for regular queries (which do not require inference), is this a good alternative? What kind of queries could benefit from the Prolog translation? Can we always use Prolog engines to execute XML queries in an efficient way? There are many questions involved in adopting an alternative approach to run XML queries. In this work, we investigate this matter by translating XML queries into Prolog queries and comparing the query processing times using Prolog and native XML engines. Our work contributes by providing a set of heuristics that helps users to decide when to use Prolog engines to process a given XML query. In summary, our results show that queries that search elements by a key value or by its position (simple search) are more efficient when run in Prolog than in native XML engines. Also, queries over large datasets, or that searches for substrings perform better when run by native XML engines.  相似文献   

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