Relevant bibliographies by topics / Ad-Hoc Information Retrieval

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  2. Dissertations / Theses
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Academic literature on the topic 'Ad-Hoc Information Retrieval'

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Published: 7 July 2024
Last updated: 7 July 2024

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Journal articles on the topic "Ad-Hoc Information Retrieval"

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Ormeño, Pablo, Marcelo Mendoza, and Carlos Valle. "Topic Models Ensembles for AD-HOC Information Retrieval." Information 12, no. 9 (2021): 360. http://dx.doi.org/10.3390/info12090360.

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Ad hoc information retrieval (ad hoc IR) is a challenging task consisting of ranking text documents for bag-of-words (BOW) queries. Classic approaches based on query and document text vectors use term-weighting functions to rank the documents. Some of these methods’ limitations consist of their inability to work with polysemic concepts. In addition, these methods introduce fake orthogonalities between semantically related words. To address these limitations, model-based IR approaches based on topics have been explored. Specifically, topic models based on Latent Dirichlet Allocation (LDA) allow building representations of text documents in the latent space of topics, the better modeling of polysemy and avoiding the generation of orthogonal representations between related terms. We extend LDA-based IR strategies using different ensemble strategies. Model selection obeys the ensemble learning paradigm, for which we test two successful approaches widely used in supervised learning. We study Boosting and Bagging techniques for topic models, using each model as a weak IR expert. Then, we merge the ranking lists obtained from each model using a simple but effective top-k list fusion approach. We show that our proposal strengthens the results in precision and recall, outperforming classic IR models and strong baselines based on topic models.
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Kurland, Oren, and Lillian Lee. "Clusters, language models, and ad hoc information retrieval." ACM Transactions on Information Systems 27, no. 3 (2009): 1–39. http://dx.doi.org/10.1145/1508850.1508851.

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Ensan, Faezeh, and Feras Al-Obeidat. "Relevance-based entity selection for ad hoc retrieval." Information Processing & Management 56, no. 5 (2019): 1645–66. http://dx.doi.org/10.1016/j.ipm.2019.05.005.

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Cai, Weihong, Zijun Hu, Yalan Luo, Daoyuan Liang, Yifan Feng, and Jiaxin Chen. "Multi-Layer Contextual Passage Term Embedding for Ad-Hoc Retrieval." Information 13, no. 5 (2022): 221. http://dx.doi.org/10.3390/info13050221.

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Nowadays, pre-trained language models such as Bidirectional Encoder Representations from Transformer (BERT) are becoming a basic building block in Information Retrieval tasks. Nevertheless, there are several limitations when applying BERT to the query-document matching task: (1) relevance assessments are applicable at the document-level, and the tokens of documents often exceed the maximum input length of BERT; (2) applying BERT to long documents leads to a great consumption of memory usage and run time, owing to the computational cost of the interactions between tokens. This paper explores a novel multi-layer contextual passage architecture that leverage text summarization extraction to generate passage-level evidence for the pre-selected document passage thus brought new possibilities for the long document relevance task. Experiments were conducted on two standard ad-hoc retrieval collections from the Text Retrieval Conference (TREC) 2004 Robust Track (Robust04) and ClueWeb09 with two different characteristics individually. Experimental results show that our approach can significantly outperform the strong baselines and even compared with the same BERT-based models, the precision of our methods as well as state-of-the-art neural ranking models.
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Cai, Weihong, Zijun Hu, Yalan Luo, Daoyuan Liang, Yifan Feng, and Jiaxin Chen. "Multi-Layer Contextual Passage Term Embedding for Ad-Hoc Retrieval." Information 13, no. 5 (2022): 221. http://dx.doi.org/10.3390/info13050221.

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Nowadays, pre-trained language models such as Bidirectional Encoder Representations from Transformer (BERT) are becoming a basic building block in Information Retrieval tasks. Nevertheless, there are several limitations when applying BERT to the query-document matching task: (1) relevance assessments are applicable at the document-level, and the tokens of documents often exceed the maximum input length of BERT; (2) applying BERT to long documents leads to a great consumption of memory usage and run time, owing to the computational cost of the interactions between tokens. This paper explores a novel multi-layer contextual passage architecture that leverage text summarization extraction to generate passage-level evidence for the pre-selected document passage thus brought new possibilities for the long document relevance task. Experiments were conducted on two standard ad-hoc retrieval collections from the Text Retrieval Conference (TREC) 2004 Robust Track (Robust04) and ClueWeb09 with two different characteristics individually. Experimental results show that our approach can significantly outperform the strong baselines and even compared with the same BERT-based models, the precision of our methods as well as state-of-the-art neural ranking models.
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Zhou, Xiaohua, Xiaohua Hu, and Xiaodan Zhang. "Topic Signature Language Models for Ad hoc Retrieval." IEEE Transactions on Knowledge and Data Engineering 19, no. 9 (2007): 1276–87. http://dx.doi.org/10.1109/tkde.2007.1058.

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Dang, Edward Kai Fung, Robert Wing Pong Luk, and James Allan. "A Comparison between Term-Independence Retrieval Models for Ad Hoc Retrieval." ACM Transactions on Information Systems 40, no. 3 (2022): 1–37. http://dx.doi.org/10.1145/3483612.

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In Information Retrieval, numerous retrieval models or document ranking functions have been developed in the quest for better retrieval effectiveness. Apart from some formal retrieval models formulated on a theoretical basis, various recent works have applied heuristic constraints to guide the derivation of document ranking functions. While many recent methods are shown to improve over established and successful models, comparison among these new methods under a common environment is often missing. To address this issue, we perform an extensive and up-to-date comparison of leading term-independence retrieval models implemented in our own retrieval system. Our study focuses on the following questions: (RQ1) Is there a retrieval model that consistently outperforms all other models across multiple collections; (RQ2) What are the important features of an effective document ranking function? Our retrieval experiments performed on several TREC test collections of a wide range of sizes (up to the terabyte-sized Clueweb09 Category B) enable us to answer these research questions. This work also serves as a reproducibility study for leading retrieval models. While our experiments show that no single retrieval model outperforms all others across all tested collections, some recent retrieval models, such as MATF and MVD, consistently perform better than the common baselines.
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Deveaud, Romain, Eric SanJuan, and Patrice Bellot. "Accurate and effective latent concept modeling for ad hoc information retrieval." Document numérique 17, no. 1 (2014): 61–84. http://dx.doi.org/10.3166/dn.17.1.61-84.

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Khodabakhsh, Maryam, and Ebrahim Bagheri. "Semantics-enabled query performance prediction for ad hoc table retrieval." Information Processing & Management 58, no. 1 (2021): 102399. http://dx.doi.org/10.1016/j.ipm.2020.102399.

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Garigliotti, Darío, Faegheh Hasibi, and Krisztian Balog. "Identifying and exploiting target entity type information for ad hoc entity retrieval." Information Retrieval Journal 22, no. 3-4 (2018): 285–323. http://dx.doi.org/10.1007/s10791-018-9346-x.

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Dissertations / Theses on the topic "Ad-Hoc Information Retrieval"

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Azzopardi, Leif. "Incorporating context within the language modeling approach for ad hoc information retrieval." Thesis, University of the West of Scotland, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427712.

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Uganda has been considered one of Africa's few "success stories" over the past decade, an example of how a country can be transformed through a committed state bureaucracy. The thesis questions this view by looking at the experiences of development and change in a subparish in eastern Uganda. From this more local-level perspective, the thesis discusses the weakness of the state in the countryside, and incorporates the importance of religious and customary institutions. In place of a narrow view of politics, focused on reforms and policies coming from above, which rarely reach rural areas in a consistent or predictable way, the thesis describes political developments within a rural community. The thesis rests on two premises. First, that the state in rural Uganda has been too weak to support an effective bureaucratic presence in the countryside. Second, that politics at the local-level is an "open-ended" business, better understood through investigating a range of institutional spaces and activities, rather than a particular set of actions, or a single bureaucracy. Oledai sub-parish, which provides the empirical material for the thesis, was far removed from the idea of state-sponsored success described in the literature. V illagers had to contend with a history of violence, with recent impoverishment, and with the reality that the rural economy was unimportant in maintaining the structures of the government system. The thesis shows that the marginalisation of the countryside came at a time when central and local government structures had become increasingly reliant on funding from abroad. Aside from the analysing the weakness of the state bureaucracy, the thesis goes on to discuss broader changes in the life of the sub-parish, including the impact of a violent insurgency in the late 1980s. The thesis also looks at the role of churches and burial societies, institutions which have been largely ignored by the literature on political developments in Uganda. Religious and customary institutions, as well as the village court, provided spaces where political goals, such as settling disputes, building a career, or acquiring wealth, could be pursued.
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Roos, Daniel. "Evaluation of BERT-like models for small scale ad-hoc information retrieval." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177675.

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Measuring semantic similarity between two sentences is an ongoing research field with big leaps being taken every year. This thesis looks at using modern methods of semantic similarity measurement for an ad-hoc information retrieval (IR) system. The main challenge tackled was answering the question "What happens when you don’t have situation-specific data?". Using encoder-based transformer architectures pioneered by Devlin et al., which excel at fine-tuning to situationally specific domains, this thesis shows just how well the presented methodology can work and makes recommendations for future attempts at similar domain-specific tasks. It also shows an example of how a web application can be created to make use of these fast-learning architectures.
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Goyal, Pawan. "Analytic knowledge discovery techniques for ad-hoc information retrieval and automatic text summarization." Thesis, Ulster University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.543897.

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Information retrieval is broadly concerned with the problem of automated searching for information within some document repository to support various information requests by users. The traditional retrieval frameworks work on the simplistic assumptions of “word independence” and “bag-of-words”, giving rise to problems such as “term mismatch” and “context independent document indexing”. Automatic text summarization systems, which use the same paradigm as that of information retrieval, also suffer from these problems. The concept of “semantic relevance” has also not been formulated in the existing literature. This thesis presents a detailed investigation of the knowledge discovery models and proposes new approaches to address these issues. The traditional retrieval frameworks do not succeed in defining the document content fully because they do not process the concepts in the documents; only the words are processed. To address this issue, a document retrieval model has been proposed using concept hierarchies, learnt automatically from a corpora. A novel approach to give a meaningful representation to the concept nodes in a learnt hierarchy has been proposed using a fuzzy logic based soft least upper bound method. A novel approach of adapting the vector space model with dependency parse relations for information retrieval also has been developed. A user query for information retrieval (IR) applications may not contain the most appropriate terms (words) as actually intended by the user. This is usually referred to as the term mismatch problem and is a crucial research issue in IR. To address this issue, a theoretical framework for Query Representation (QR) has been developed through a comprehensive theoretical analysis of a parametric query vector. A lexical association function has been derived analytically using the relevance criteria. The proposed QR model expands the user query using this association function. A novel term association metric has been derived using the Bernoulli model of randomness. x The derived metric has been used to develop a Bernoulli Query Expansion (BQE) model. The Bernoulli model of randomness has also been extended to the pseudo relevance feedback problem by proposing a Bernoulli Pseudo Relevance (BPR) model. In the traditional retrieval frameworks, the context in which a term occurs is mostly overlooked in assigning its indexing weight. This results in context independent document indexing. To address this issue, a novel Neighborhood Based Document Smoothing (NBDS) model has been proposed, which uses the lexical association between terms to provide a context sensitive indexing weight to the document terms, i.e. the term weights are redistributed based on the lexical association with the context words. To address the “context independent document indexing” for sentence extraction based text summarization task, a lexical association measure derived using the Bernoulli model of randomness has been used. A new approach using the lexical association between terms has been proposed to give a context sensitive weight to the document terms and these weights have been used for the sentence extraction task. Developed analytically, the proposed QR, BQE, BPR and NBDS models provide a proper mathematical framework for query expansion and document smoothing techniques, which have largely been heuristic in the existing literature. Being developed in the generalized retrieval framework, as also proposed in this thesis, these models are applicable to all of the retrieval frameworks. These models have been empirically evaluated over the benchmark TREC datasets and have been shown to provide significantly better performance than the baseline retrieval frameworks to a large degree, without adding significant computational or storage burden. The Bernoulli model applied to the sentence extraction task has also been shown to enhance the performance of the baseline text summarization systems over the benchmark DUC datasets. The theoretical foundations alongwith the empirical results verify that the proposed knowledge discovery models in this thesis advance the state of the art in the field of information retrieval and automatic text summarization.
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Phillips, Robert H. "The effect of denormalized schemas on ad-hoc query formulation: a human factors experiment in database design." Diss., Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/54262.

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The information systems literature is rich with studies of database organization and its impact on machine, programmer, and administrative efficiency. Little attention, however, has been paid to the impact of database organization on end-user interactions with computer systems. This research effort addressed this increasingly important issue by examining the effects of database organization on the ability of end-users to locate and extract desired information. The study examined the impact of normalization levels of external relational database schema on end-user query success. It has been suggested in the literature that end-user query success might be improved by presenting external schema in lower level normal forms. This speculation is based on an analytical study of one particular class of query, queries involving join operations. The research presented here provides empirical support for this assertion. However, the implicit assumption that all other queries are neutral in their bias toward a particular level of normalization was found to be false. A class of queries requiring decomposition of prejoined relations was identified which strongly biases normalized relations. Thus, no particular normalization level was shown to dominate unless assumptions were made as to the class of query being formulated. Evidence from field research may be required to completely resolve the issue. The study also examined the interaction effects between normalization levels and other key variables known to impact query success. Significant interactions with user skill and the complexity of the query being made were found. The level of normalization did not impact high skilled users making easy queries or low skilled users making difficult queries. The impact of these interactions, as well as the main effects of the related variables, on query syntax and logic errors holds important implications for database administrators as well as those involved with the development of database query languages.<br>Ph. D.
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Audeh, Bissan. "Reformulation sémantique des requêtes pour la recherche d’information ad hoc sur le Web." Thesis, Saint-Etienne, EMSE, 2014. http://www.theses.fr/2014EMSE0750/document.

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Dans le cadre d’une solution de modification de la requête, nous nous intéressons aux différentes façons d’utiliser la sémantique pour mieux exprimer le besoin d’information de l’utilisateur dans un contexte Web. Nous distinguons deux types de concepts : ceux identifiables dans une ressource sémantique comme une ontologie, et ceux que l’on extrait à partir d’un ensemble de documents de pseudo retour de pertinence. Nous proposons une Approche Sémantique Mixte d’Expansion et de Reformulation (ASMER) qui permet de modéliser l’utilisation de ces deux types de concepts dans une requête modifiée. Cette approche considère plusieurs défis liés à la modification automatique des requêtes, notamment le choix sélectif des termes d’expansion, le traitement des entités nommées et la reformulation de la requête finale.Bien que dans un contexte Web la précision soit le critère d’évaluation le plus adapté, nous avons aussi pris en compte le rappel pour étudier le comportement de notre approche sous plusieurs aspects. Ce choix a suscité une autre problématique liée à l’évaluation du rappel en recherche d’information. En constatant que les mesures précédentes ne répondent pas à nos contraintes, nous avons proposé la mesure MOR (Mesure Orientée Rappel), qui permet d’évaluer le rappel en tenant compte de la précision comme importante mais pas prioritaire dans un contexte dirigé rappel.En incluant MOR dans notre stratégie de test, nous avons évalué ASMER sur quatre collections Web issues des campagnes INEX et TREC. Nos expériences montrent qu’ASMER améliore la performance en précision par rapport aux requêtes originales et par rapport aux requêtes étendues par une méthode de l’état de l’art<br>As a query expansion and reformulation solution, we are interested in the different ways the semantic could be used to translate users information need into a query. We define two types of concepts : those which we can identify in a semantic resource like an ontology, and the ones we extract from the collection of documents via pseudo relevance feedback procedure. We propose a semantic and mixed approach to query expansion and reformulation (ASMER) that allows to integrate these two types of concepts in an automatically modified query. Our approach considers many challenges, especially selective terms expansion, named entity treatment and query reformulation.Even though the precision is the evaluation criteria the most adapted to a web context, we also considered evaluating the recall to study the behavior of our model from different aspects. This choice led us to handle a different problem related to evaluating the recall in information retrieval. After realizing that actual measures don't satisfy our constraints, we proposed a new recall oriented measure (MOR) which considers the recall as a priority without ignoring the precision.Among other measures, MOR was considered to evaluate our approach ASMER on four web collection from the standard evaluation campaigns Inex and Trec. Our experiments showed that ASMER improves the precision of the non modified original queries. In most cases, our approach achieved statistically significant enhancements when compared to a state of the art query expansion method. In addition, ASMER retrieves the first relevant document in better ranks than the compared approaches, it also has slightly better recall according to the measure MOR
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Ayoub, Oussama. "Enrichissement sémantique non supervisé de longs documents spécialisés pour la recherche d’information." Electronic Thesis or Diss., Paris, HESAM, 2023. http://www.theses.fr/2023HESAC039.

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Face à l'accroissement incessant des données textuelles à traiter, les systèmes de Recherche d'Information (RI) doivent faire face à l'adaptation des mécanismes existants pour une sélection pertinente des ensembles documentaires dédiés à un contexte spécifique. Une difficulté prépondérante réside dans la divergence terminologique entre les termes employés dans les requêtes et ceux présents dans les documents. Cette disparité sémantique, particulièrement prononcée pour les termes de sens proches dans les documents issus de domaines spécialisés de grande taille, pose un défi significatif en RI. Face à ces enjeux, de nombreuses études se sont limitées à l'enrichissement de requêtes via des modèles supervisés, une approche qui s'avère inadéquate pour une application industrielle et manque de flexibilité. Cette thèse propose une alternative novatrice avec un système de recherche non supervisé basé sur des méthodes d'Apprentissage Profond. La plateforme LoGE utilise un modèle de langage masqué pour extrapoler des termes associés, enrichissant ainsi la représentation textuelle des documents. Les modèles utilisés sont entraînés préalablement sur de vastes corpus textuels, intégrant des connaissances générales ou spécifiques à un domaine, optimisant ainsi la représentation des documents. L'analyse des extensions générées a révélé un déséquilibre entre le signal (termes pertinents ajoutés) et le bruit (termes non pertinents). Pour pallier ce problème, nous avons développé SummVD, une approche de résumé automatique extractif, utilisant la décomposition en valeurs singulières pour synthétiser l'information contenue dans les documents et identifier les phrases les plus pertinentes. Cette méthode a été adaptée pour filtrer les termes des extensions en fonction du contexte local de chaque document, afin de maintenir la pertinence de l'information tout en minimisant le bruit<br>Faced with the incessant growth of textual data that needs processing, Information Retrieval (IR) systems are confronted with the urgent need to adopt effective mechanisms for efficiently selecting document sets that are best suited to specific queries. A predominant difficulty lies in the terminological divergence between the terms used in queries and those present in relevant documents. This semantic disparity, particularly pronounced for terms with similar meanings in large-scale documents from specialized domains, poses a significant challenge for IR systems.In addressing these challenges, many studies have been limited to query enrichment via supervised models, an approach that proves inadequate for industrial application and lacks flexibility. This thesis proposes LoGE an innovative alternative with an unsupervised search system based on advanced Deep Learning methods. This system uses a masked language model to extrapolate associated terms, thereby enriching the textual representation of documents. The Deep Learning models used, pre-trained on extensive textual corpora, incorporate general or domain-specific knowledge, thus optimizing the document representation.The analysis of the generated extensions revealed an imbalance between the signal (relevant terms added) and the noise (irrelevant terms). To address this issue, we developed SummVD, an innovative extractive automatic summarization approach, using singular value decomposition to synthesize the information contained in documents and identify the most pertinent phrases. This method has been adapted to filter the terms of the extensions based on the local context of each document, thereby maintaining the relevance of the information while minimizing noise
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Cheng, Yuan-Po, and 鄭元博. "Retrieval-Guaranteed Information Brokerage Schemes in 3D Wireless Ad Hoc Networks." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/14644935019115558287.

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博士<br>國立清華大學<br>資訊工程學系<br>101<br>In this dissertation, I address the problem of information brokerage, where information consumers search for the data acquired by information producers. To the best of my knowledge, there exists no retrieval-guaranteed location-aware information brokerage scheme with a bounded data retrieval path length and bounded replication and retrieval message overhead costs available for use in 3D wireless ad hoc networks to date. In this dissertation, I propose a novel location-aware information brokerage scheme, termed LAIB, where the network area is divided into cube grids, and data are replicated and retrieved in the hashed geographic location in each grid designated by the producer and the consumer, respectively. In LAIB, a polylogarithmic number of grids are designated by the producer and by the consumer, and at least one grid, whose distance from the grid of the consumer is smaller than the distance from the grid of the consumer to the grid of the producer, is designated by both the producer and the consumer. Simulations show that, as the network area is divided into a moderate number of grids, LAIB has good performance in term of retrieval latency stretch while ensuring moderate replication memory, replication message, and retrieval message overhead costs.
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Lu, Hong. "Optimization Algorithms for Information Retrieval and Transmission in Distributed Ad Hoc Networks." 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-187.

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An ad hoc network is formed by a group of self-configuring nodes, typically deployed in two or three dimensional spaces, and communicating with each other through wireless or some other media. The distinct characteristics of ad hoc networks include the lack of pre-designed infrastructure, the natural correlation between the network topology and geometry, and limited communication and computation resources. These characteristics introduce new challenges and opportunities for de- signing ad hoc network applications. This dissertation studies various optimization problems in ad hoc network information retrieval and transmission. Information stored in ad hoc networks is naturally associated with its location. To effectively retrieve such information, we study two fundamental problems, range search and object locating, from a distance sensitive point of view, where the retrieval cost depends on the distance between the user and the target information. We develop a general framework that is applicable to both problems for optimizing the storage overhead while maintaining the distance sensitive retrieval requirement. In addition, we derive a lowerbound result for the object locating problem which shows that logarithmic storage overhead is asymptotically optimal to achieve linear retrieval cost for growth bounded networks. Bandwidth is a scarce resource for wireless ad hoc networks, and its proper utilization is crucial to effective information transmission. To avoid conflict of wireless transmissions, links need to be carefully scheduled to satisfy various constraints. In this part of the study, we first consider an optimization problem of end-to-end on- demand bandwidth allocation with the single transceiver constraint. We study its complexity and present a 2-approximation algorithm. We then discuss how to estimate the end-to-end throughput under a widely adopted model for radio signal interference. A method based on identifying certain clique patterns is proposed and shown to have good practical performance.
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Wu, Chia-Yi, and 吳佳怡. "Retrieval-Guaranteed Location-Aware Information Brokerage Scheme in 3D Wireless Ad Hoc Networks." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/32208728857110953630.

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Roegiest, Adam. "Finding Microblog Posts of User Interest." Thesis, 2012. http://hdl.handle.net/10012/6633.

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Microblogging is an increasingly popular form of social media. One of the most popular microblogging services is Twitter. The number of messages posted to Twitter on a daily basis is extremely large. Accordingly, it becomes hard for users to sort through these messages and find ones that interest them. Twitter offers search mechanisms but they are relatively simple and accordingly the results can be lacklustre. Through participation in the 2011 Text Retrieval Conference's Microblog Track, this thesis examines real-time ad hoc search using standard information retrieval approaches without microblog or Twitter specific modifications. It was found that using pseudo-relevance feedback based upon a language model derived from Twitter posts, called tweets, in conjunction with standard ranking methods is able to perform competitively with advanced retrieval systems as well as microblog and Twitter specific retrieval systems. Furthermore, possible modifications both Twitter specific and otherwise are discussed that would potentially increase retrieval performance. Twitter has also spawned an interesting phenomenon called hashtags. Hashtags are used by Twitter users to denote that their message belongs to a particular topic or conversation. Unfortunately, tweets have a 140 characters limit and accordingly all relevant hashtags cannot always be present in tweet. Thus, Twitter users cannot easily find tweets that do not contain hashtags they are interested in but should contain them. This problem is investigated in this thesis in three ways using learning methods. First, learning methods are used to determine if it is possible to discriminate between two topically different sets of a tweets. This thesis then investigates whether or not it is possible for tweets without a particular hashtag, but discusses the same topic as the hashtag, to be separated from random tweets. This case mimics the real world scenario of users having to sift through random tweets to find tweets that are related to a topic they are interested in. This investigation is performed by removing hashtags from tweets and attempting to distinguish those tweets from random tweets. Finally, this thesis investigates whether or not topically similar tweets can also be distinguished based upon a sub-topic. This was investigated in almost an identical manner to the second case. This thesis finds that topically distinct tweets can be distinguished but more importantly that standard learning methods are able to determine that a tweet with a hashtag removed should have that hashtag. In addition, this hashtag reconstruction can be performed well with very few examples of what a tweet with and without the particular hashtag should look like. This provides evidence that it may be possible to separate tweets a user may be interested from random tweets only using hashtags they are interested in. Furthermore, the success of the hashtag reconstruction also provides evidence that users do not misuse or abuse hashtags since hashtag presence was taken to be the ground truth in all experiments. Finally, the applicability of the hashtag reconstruction results to the TREC Microblog Track and a mobile application is presented.
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Books on the topic "Ad-Hoc Information Retrieval"

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Programme, United Nations Environment, and Global Environmental Monitoring System, eds. Report of an ad hoc working group on GRID systems and software: UNEP, Nairobi, 26-27 July 1990. United Nations Environment Programme, 1990.

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Symeon, Papavassiliou, Ruehrup Stefan, and SpringerLink (Online service), eds. Ad-hoc, Mobile, and Wireless Networks: 11th International Conference, ADHOC-NOW 2012, Belgrade, Serbia, July 9-11, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Cichoń, Jacek. Ad-hoc, Mobile, and Wireless Network: 12th International Conference, ADHOC-NOW 2013, Wrocław, Poland, July 8-10, 2013. Proceedings. Springer Berlin Heidelberg, 2013.

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Frey, Hannes. Ad-hoc, Mobile, and Wireless Networks: 10th International Conference, ADHOC-NOW 2011, Paderborn, Germany, July 18-20, 2011. Proceedings. Springer-Verlag GmbH Berlin Heidelberg, 2011.

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David, Hutchison. Resilient Networks and Services: Second International Conference on Autonomous Infrastructure, Management and Security, AIMS 2008 Bremen, Germany, July 1-3, 2008 Proceedings. Springer-Verlag Berlin Heidelberg, 2008.

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ADHOC-NOW, 2010 (2010 Edmonton Alta ). Ad-hoc, mobile and wireless networks: 9th international conference, ADHOC-NOW 2010, Edmonton, AB, Canada, August 20-22, 2010 : proceedings. Springer, 2010.

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Evangelos, Kranakis, and Opatrny Jaroslav, eds. Ad-hoc, mobile, and wireless networks: 6th international conference, ADHOC-NOW 2007, Morelia, Mexico, September 24-26, 2007 ; proceedings. Springer, 2007.

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1959-, Fdida Serge, and Sugiura Kazunori, eds. Sustainable internet: Third Asian Internet Engineering Conference, AINTEC 2007, Phuket, Thailand, November 27-29, 2007 : proceedings. Springer, 2007.

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Wolfgang, Karl, Yehia Sami, and SpringerLink (Online service), eds. Architecture of Computing Systems - ARCS 2010: 23rd International Conference, Hannover, Germany, February 22-25, 2010. Proceedings. Springer-Verlag Berlin Heidelberg, 2010.

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International, Conference on Distributed Computing and Internet Technology (6th 2010 Bhubaneswar India). Distributed computing and internet technology: 6th international conference, ICDCIT 2010, Bhubaneswar, India, February 15-17, 2010 : proceedings. Springer, 2010.

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Book chapters on the topic "Ad-Hoc Information Retrieval"

1

Habibian, AmirHossein, Abolfazl AleAhmad, and Azadeh Shakery. "Ad Hoc Information Retrieval for Persian." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15754-7_13.

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Akasereh, Mitra, and Jacques Savoy. "Ad Hoc Retrieval with Marathi Language." In Multilingual Information Access in South Asian Languages. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40087-2_3.

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Kwok, Kui-Lam, Laszlo Grunfeld, and Peter Deng. "Improving Weak Ad-Hoc Retrieval by Web Assistance and Data Fusion." In Information Retrieval Technology. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11562382_2.

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Di Nunzio, Giorgio M., Nicola Ferro, Thomas Mandl, and Carol Peters. "CLEF 2006: Ad Hoc Track Overview." In Evaluation of Multilingual and Multi-modal Information Retrieval. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74999-8_3.

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Hirakawa, Koji, Kotaro Kikuchi, Kazuya Ueki, Tetsunori Kobayashi, and Yoshihiko Hayashi. "Ad-hoc Video Search Improved by the Word Sense Filtering of Query Terms." In Information Retrieval Technology. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03520-4_15.

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Vo, Duc-Thuan, Fattane Zarrinkalam, Ba Pham, Negar Arabzadeh, Sara Salamat, and Ebrahim Bagheri. "Neural Ad-Hoc Retrieval Meets Open Information Extraction." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28238-6_57.

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Pantziou, Grammati, Aristides Mpitziopoulos, Damianos Gavalas, Charalampos Konstantopoulos, and Basilis Mamalis. "Mobile Sinks for Information Retrieval from Cluster-Based WSN Islands." In Ad-Hoc, Mobile and Wireless Networks. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04383-3_16.

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Sun, Qiang, JiaLiang Wu, and Yue Wu. "A Multidimensional Interaction-Focused Model for Ad-Hoc Retrieval." In Neural Information Processing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04179-3_23.

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McNamee, Paul. "JHU/APL Ad Hoc Experiments at CLEF 2006." In Evaluation of Multilingual and Multi-modal Information Retrieval. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74999-8_22.

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Tu, Xinhui, Jing Luo, Bo Li, Tingting He, and Jinguang Gu. "Positional Translation Language Model for Ad-Hoc Information Retrieval." In Advances in Knowledge Discovery and Data Mining. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06605-9_12.

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Conference papers on the topic "Ad-Hoc Information Retrieval"

1

Shen, Xuehua, and ChengXiang Zhai. "Active feedback in ad hoc information retrieval." In the 28th annual international ACM SIGIR conference. ACM Press, 2005. http://dx.doi.org/10.1145/1076034.1076047.

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Ma, Zhengyi, Zhicheng Dou, Wei Xu, et al. "Pre-training for Ad-hoc Retrieval." In CIKM '21: The 30th ACM International Conference on Information and Knowledge Management. ACM, 2021. http://dx.doi.org/10.1145/3459637.3482286.

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Ye, Zheng, Jimmy Xiangji Huang, and Jun Miao. "A hybrid model for ad-hoc information retrieval." In the 35th international ACM SIGIR conference. ACM Press, 2012. http://dx.doi.org/10.1145/2348283.2348451.

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Bradford, Roger. "Incorporating Ad Hoc Phrases in LSI Queries." In International Conference on Knowledge Discovery and Information Retrieval. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0005073300610070.

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Kurland, Oren, and Lillian Lee. "Corpus structure, language models, and ad hoc information retrieval." In the 27th annual international conference. ACM Press, 2004. http://dx.doi.org/10.1145/1008992.1009027.

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Vuurens, Jeroen B. P., Arjen P. de Vries, Roi Blanco, and Peter Mika. "Online News Tracking for Ad-Hoc Information Needs." In ICTIR '15: ACM SIGIR International Conference on the Theory of Information Retrieval. ACM, 2015. http://dx.doi.org/10.1145/2808194.2809474.

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Li, Chongyang. "Semantic Augmentation Transformer Model for Ad-hoc Retrieval." In 2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC). IEEE, 2022. http://dx.doi.org/10.1109/itoec53115.2022.9734522.

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Fan, Yixing, Jiafeng Guo, Yanyan Lan, Jun Xu, Chengxiang Zhai, and Xueqi Cheng. "Modeling Diverse Relevance Patterns in Ad-hoc Retrieval." In SIGIR '18: The 41st International ACM SIGIR conference on research and development in Information Retrieval. ACM, 2018. http://dx.doi.org/10.1145/3209978.3209980.

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Kato, Makoto P., Hiroaki Ohshima, Ying-Hsang Liu, and Hsin-Liang Chen. "A Test Collection for Ad-hoc Dataset Retrieval." In SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2021. http://dx.doi.org/10.1145/3404835.3463261.

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Tu, Xinhui, Jing Luo, Bo Li, and Tingting He. "Log-Bilinear Document Language Model for Ad-hoc Information Retrieval." In CIKM '14: 2014 ACM Conference on Information and Knowledge Management. ACM, 2014. http://dx.doi.org/10.1145/2661829.2661919.

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