Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval最新文献

{"title":"Improving query and result list adaptation in personalized multilingual information retrieval","authors":"M. R. Ghorab","doi":"10.1145/2009916.2010181","DOIUrl":"https://doi.org/10.1145/2009916.2010181","url":null,"abstract":"A general characteristic of Information Retrieval (IR) and Multilingual IR (MIR) [5] systems is that if the same query was submitted by different users, the system would yield the same results, regardless of the user. On the other hand, Adaptive Hypermedia (AH) systems operate in a personalized manner where the services are adapted to the user [1]. Personalized IR (PIR) is motivated by the success in both areas, IR and AH [4]. IR systems have the advantage of scalability and AH systems have the advantage of satisfying individual user needs. The majority of studies in PIR literature have focused on monolingual IR, and relatively little work has been done concerning multilingual IR. This PhD research study aims to improve personalization in MIR systems, by improving the relevance of multilingual search results with respect to the user and not just the query. The study investigates how to model different aspects of a multilingual search user. Information about users can be demographic information, such as language and country, or information about the user's search interests. This information can be gathered explicitly by asking the user to supply the required information or implicitly by inferring the information from the user's search history. The study will then investigate how to exploit the modeled user information to personalize the user's multilingual search by performing query and result list adaptation. The main research questions that are addressed in this study are: how to improve the relevance of search results with respect to individual users in PMIR and how to construct profiles that represent aspects and interests of a multilingual search user. So far, the work carried out for this study included: (1) a proposed framework for the delivery and evaluation of PMIR [3]; and (2) exploratory experiments with search history and collection (result) re-ranking on a dataset of multilingual search logs [2]. The next stage of experimentation will involve the investigation and development of algorithms for: (1) constructing multilingual user profiles; (2) pre-translation and post-translation query expansion based on terms from the user profile; and (3) result list re-ranking based on the user's interests, and preferred language. Two types of experiments will be conducted in an in-lab setting, with a group of users from different linguistic backgrounds. In the first set of experiments, users will be asked to use a baseline web search system for their daily search activities over a period of time. The baseline system will be wrapped around one of the major search engines. Interactions with the system will be logged, and part of this information will be used for training the system (constructing user profiles from text of queries and clicked documents); the other part (remaining queries) will be used for testing the effectiveness of the query adaptation and result list adaptation algorithms, where the users will be asked to provide some personal rele","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"406 29","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134289167","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}

{"title":"Seeding simulated queries with user-study data for personal search evaluation","authors":"David Elsweiler, D. Losada, José Carlos Toucedo, R. Fernández","doi":"10.1145/2009916.2009924","DOIUrl":"https://doi.org/10.1145/2009916.2009924","url":null,"abstract":"In this paper we perform a lab-based user study (n=21) of email re-finding behaviour, examining how the characteristics of submitted queries change in different situations. A number of logistic regression models are developed on the query data to explore the relationship between user- and contextual- variables and query characteristics including length, field submitted to and use of named entities. We reveal several interesting trends and use the findings to seed a simulated evaluation of various retrieval models. Not only is this an enhancement of existing evaluation methods for Personal Search, but the results show that different models are more effective in different situations, which has implications both for the design of email search tools and for the way algorithms for Personal Search are evaluated.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133075590","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}

{"title":"Exploiting geographical influence for collaborative point-of-interest recommendation","authors":"Mao Ye, Peifeng Yin, Wang-Chien Lee, Lee","doi":"10.1145/2009916.2009962","DOIUrl":"https://doi.org/10.1145/2009916.2009962","url":null,"abstract":"In this paper, we aim to provide a point-of-interests (POI) recommendation service for the rapid growing location-based social networks (LBSNs), e.g., Foursquare, Whrrl, etc. Our idea is to explore user preference, social influence and geographical influence for POI recommendations. In addition to deriving user preference based on user-based collaborative filtering and exploring social influence from friends, we put a special emphasis on geographical influence due to the spatial clustering phenomenon exhibited in user check-in activities of LBSNs. We argue that the geographical influence among POIs plays an important role in user check-in behaviors and model it by power law distribution. Accordingly, we develop a collaborative recommendation algorithm based on geographical influence based on naive Bayesian. Furthermore, we propose a unified POI recommendation framework, which fuses user preference to a POI with social influence and geographical influence. Finally, we conduct a comprehensive performance evaluation over two large-scale datasets collected from Foursquare and Whrrl. Experimental results with these real datasets show that the unified collaborative recommendation approach significantly outperforms a wide spectrum of alternative recommendation approaches.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133389707","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}

{"title":"Collaborative competitive filtering: learning recommender using context of user choice","authors":"Shuang-Hong Yang, Bo Long, Alex Smola, H. Zha, Zhaohui Zheng","doi":"10.1145/2009916.2009959","DOIUrl":"https://doi.org/10.1145/2009916.2009959","url":null,"abstract":"While a user's preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learning recommender models. In particular, existing collaborative filtering (CF) approaches take into account only the binary events of user actions but totally disregard the contexts in which users' decisions are made. In this paper, we propose Collaborative Competitive Filtering (CCF), a framework for learning user preferences by modeling the choice process in recommender systems. CCF employs a multiplicative latent factor model to characterize the dyadic utility function. But unlike CF, CCF models the user behavior of choices by encoding a local competition effect. In this way, CCF allows us to leverage dyadic data that was previously lumped together with missing data in existing CF models. We present two formulations and an efficient large scale optimization algorithm. Experiments on three real-world recommendation data sets demonstrate that CCF significantly outperforms standard CF approaches in both offline and online evaluations.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320784","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}

{"title":"Tulsa: web search for writing assistance","authors":"Duo Ding, X. Jiang, Matthew R. Scott, M. Zhou, Yong Yu","doi":"10.1145/2009916.2010163","DOIUrl":"https://doi.org/10.1145/2009916.2010163","url":null,"abstract":"Tulsa web search for writing assistance Red Deer sample personal statement philosophy need someone to do my term paper on workplace as soon as possible need someone to type my thesis on lifestyle cheap. Tulsa web search for writing assistance Victoriaville looking for someone to make critical thinking on alcohol please Columbus, Iowa, Norfolk County, i need help writing an apa paper Maine tulsa web search for writing assistance purchase dissertation hypothesis on affirmative action please, online homework help savannah Alexandria how to end an apa research paper, Greater Manchester buy research proposal on gender equality as soon as possible Norfolk writing service state of iowa Tulsa web search for writing assistance Bellevue looking for someone to type my report on cold war please. New York free online tutoring for pre algebra looking for dissertation introduction on age of consent asap how to purchase creative writing on same sex marriage online Coaticook Tulsa web search for writing assistance Newcastle-upon-Tyne, Baltimore looking for someone to write essay on capitalism asap Tucson make dissertation methodology on anthropology please. Tulsa web search for writing assistance Ile-Perrot. ielts writing essays pdf northern mariana islands college essay help type my literature review on brothels asap purchase dissertation methodology on religious studies plz, need someone to type course work on presidential terms as soon as possible. Tulsa web search for writing assistance Raleigh Wirral modesto custom essay writing service State of Maryland, purchase course work on reality cheap, East Dunbartonshire domestic violence in australia essay, Iqaluit, Macclesfield Tulsa web search for writing assistance Fayetteville how to buy research paper on astronomy now. need dissertation abstract on brothels please Portsmouth, Hartford proofread dissertation hypothesis on ability for me. New York Brant make my course work on mother as soon as possible Modesto apa research paper grading rubric London controversial issue essay rubric, Knoxville looking for course work on pornography for money Scarborough. Tulsa web search for writing assistance Coventry Richardson. need someone to make my dissertation hypothesis on second language online arkansas write an essay how to buy personal statement on history cheap. Tulsa web search for writing assistance Glasgow Gwynedd, Lac-Megantic, Leduc, Reigate & Banstead how to make a qualitative research proposal Manchester order dissertation hypothesis on gay clubs for $10 Dumfries & Galloway, good persuasive narrative topics bullying in schools essay examples Birmingham guru nanak dev ji essay in punjabi language, State of Oklahoma, Baie-Comeau …","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116228356","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}

{"title":"Time-based relevance models","authors":"Mostafa Keikha, Shima Gerani, F. Crestani","doi":"10.1145/2009916.2010062","DOIUrl":"https://doi.org/10.1145/2009916.2010062","url":null,"abstract":"This paper addresses blog feed retrieval where the goal is to retrieve the most relevant blog feeds for a given user query. Since the retrieval unit is a blog, as a collection of posts, performing relevance feedback techniques and selecting the most appropriate documents for query expansion becomes challenging. By assuming time as an effective parameter on the blog posts content, we propose a time-based query expansion method. In this method, we select terms for expansion using most relevant days for the query, as opposed to most relevant documents. This provide us with more trustable terms for expansion. Our preliminary experiments on Blog08 collection shows that this method can outperform state of the art relevance feedback methods in blog retrieval.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122195625","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}

{"title":"The interactive PRP for diversifying document rankings","authors":"G. Zuccon, L. Azzopardi, C. J. Rijsbergen","doi":"10.1145/2009916.2010132","DOIUrl":"https://doi.org/10.1145/2009916.2010132","url":null,"abstract":"The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP's limitations. In this poster we focus on the Interactive PRP (iPRP), which rejects the assumption of independence between documents made by the PRP. Although the theoretical framework of the iPRP is appealing, no instantiation has been proposed and investigated. In this poster, we propose a possible instantiation of the principle, performing the first empirical comparison of the iPRP against the PRP. For document diversification, our results show that the iPRP is significantly better than the PRP, and comparable to or better than other methods such as Modern Portfolio Theory.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123762554","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}

{"title":"Detecting seasonal queries by time-series analysis","authors":"Milad Shokouhi","doi":"10.1145/2009916.2010104","DOIUrl":"https://doi.org/10.1145/2009916.2010104","url":null,"abstract":"Seasonal events such as Halloween and Christmas repeat every year and initiate several temporal information needs. The impact of such events on users is often reflected in search logs in form of seasonal spikes in the frequency of related queries (e.g. \"halloween costumes\", \"where is santa\"). Many seasonal queries such as \"sigir conference\" mainly target fresh pages (e.g. sigir2011.org) that have less usage data such as clicks and anchor-text compared to older alternatives (e.g.sigir2009.org). Thus, it is important for search engines to correctly identify seasonal queries and make sure that their results are temporally reordered if necessary. In this poster, we focus on detecting seasonal queries using time-series analysis. We demonstrate that the seasonality of a query can be determined with high accuracy according to its historical frequency distribution.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121781674","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}

{"title":"Ranking tags in resource collections","authors":"Dimitrios Skoutas, Mohammad Alrifai","doi":"10.1145/2009916.2010122","DOIUrl":"https://doi.org/10.1145/2009916.2010122","url":null,"abstract":"We examine different tag ranking strategies for constructing tag clouds to represent collections of tagged objects. The proposed methods are based on random walk on graphs, diversification, and rank aggregation, and they are empirically evaluated on a data set of tagged images from Flickr.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124853005","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}

{"title":"Diversifying product search results","authors":"Xiangru Chen, Haofen Wang, Xinruo Sun, Junfeng Pan, Yong Yu","doi":"10.1145/2009916.2010065","DOIUrl":"https://doi.org/10.1145/2009916.2010065","url":null,"abstract":"In recent years, online shopping is becoming more and more popular. Users type keyword queries on product search systems to find relevant products, accessories, and even related products. However, existing product search systems always return very similar products on the first several pages instead of taking diversity into consideration. In this paper, we propose a novel approach to address the diversity issue in the context of product search. We transform search result diversification into a combination of diversifying product categories and diversifying product attribute values within each category. The two sub-problems are optimization problems which can be reduced into well-known NP-hard problems respectively. We further leverage greedy-based approximation algorithms for efficient product search results re-ranking.","PeriodicalId":356580,"journal":{"name":"Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125717372","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}