Post processing of multimedia information - concepts, problems, and techniques

Currently, most research work on multimedia information processing is focused on multimedia information storage and retrieval, especially indexing and content-based access of multimedia information. We consider multimedia information processing should include one more level-post-processing. Here &quot;post-processing&quot; means further processing of retrieved multimedia information, which includes fusion of multimedia information and reasoning with multimedia information to reach new conclusions. In this paper, the three levels of multimedia information processing storage, retrieval, and post-processing- are discussed. The concepts and problems of multimedia information post-processing are identified. Potential techniques that can be used in post-processing are suggested, By highlighting the problems in multimedia information post-processing, hopefully this paper will stimulate further research on this important but ignored topic.<br /

Spoken query processing for interactive information retrieval

It has long been recognised that interactivity improves the effectiveness of information retrieval systems. Speech is the most natural and interactive medium of communication and recent progress in speech recognition is making it possible to build systems that interact with the user via speech. However, given the typical length of queries submitted to information retrieval systems, it is easy to imagine that the effects of word recognition errors in spoken queries must be severely destructive on the system's effectiveness. The experimental work reported in this paper shows that the use of classical information retrieval techniques for spoken query processing is robust to considerably high levels of word recognition errors, in particular for long queries. Moreover, in the case of short queries, both standard relevance feedback and pseudo relevance feedback can be effectively employed to improve the effectiveness of spoken query processing

An overview of selected information storage and retrieval issues in computerized document processing

The rapid development of computerized information storage and retrieval techniques has introduced the possibility of extending the word processing concept to document processing. A major advantage of computerized document processing is the relief of the tedious task of manual editing and composition usually encountered by traditional publishers through the immense speed and storage capacity of computers. Furthermore, computerized document processing provides an author with centralized control, the lack of which is a handicap of the traditional publishing operation. A survey of some computerized document processing techniques is presented with emphasis on related information storage and retrieval issues. String matching algorithms are considered central to document information storage and retrieval and are also discussed

Elaboration over a Discourse Facilitates Retrieval in Sentence Processing.

Language comprehension requires access to stored knowledge and the ability to combine knowledge in new, meaningful ways. Previous work has shown that processing linguistically more complex expressions ('Texas cattle rancher' vs. 'rancher') leads to slow-downs in reading during initial processing, possibly reflecting effort in combining information. Conversely, when this information must subsequently be retrieved (as in filler-gap constructions), processing is facilitated for more complex expressions, possibly because more semantic cues are available during retrieval. To follow up on this hypothesis, we tested whether information distributed across a short discourse can similarly provide effective cues for retrieval. Participants read texts introducing two referents (e.g., two senators), one of whom was described in greater detail than the other (e.g., 'The Democrat had voted for one of the senators, and the Republican had voted for the other, a man from Ohio who was running for president'). The final sentence (e.g., 'The senator who the {Republican/Democrat}had voted for…') contained a relative clause picking out either the Many-Cue referent (with 'Republican') or the One-Cue referent (with 'Democrat'). We predicted facilitated retrieval (faster reading times) for the Many-Cue condition at the verb region ('had voted for'), where readers could understand that 'The senator' is the object of the verb. As predicted, this pattern was observed at the retrieval region and continued throughout the rest of the sentence. Participants also completed the Author/Magazine Recognition Tests (ART/MRT; Stanovich and West, 1989), providing a proxy for world knowledge. Since higher ART/MRT scores may index (a) greater experience accessing relevant knowledge and/or (b) richer/more highly structured representations in semantic memory, we predicted it would be positively associated with effects of elaboration on retrieval. We did not observe the predicted interaction between ART/MRT scores and Cue condition at the retrieval region, though ART/MRT interacted with Cue condition in other locations in the sentence. In sum, we found that providing more elaborative information over the course of a text can facilitate retrieval for referents, consistent with a framework in which referential elaboration over a discourse and not just local linguistic information directly impacts information retrieval during sentence processing

Natural Language Processing for Information Retrieval and Knowledge Discovery

Natural Language Processing (NLP) is a powerful technology for the vital tasks of information retrieval (IR) and knowledge discovery (KD) which, in turn, feed the visualization systems of the present and future and enable knowledge workers to focus more of their time on the vital tasks of analysis and prediction.published or submitted for publicatio

Combining Text and Formula Queries in Math Information Retrieval: Evaluation of Query Results Merging Strategies

Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies combining math and standard textual keyword terms in a query are given. It is shown that techniques similar to those known from textual query processing may be applied in math information retrieval as well, and lead to a cutting edge performance. Striping and merging partial results from subqueries is one technique that improves results measured by information retrieval evaluation metrics like Bpref

Multimodal music information processing and retrieval: survey and future challenges

Towards improving the performance in various music information processing tasks, recent studies exploit different modalities able to capture diverse aspects of music. Such modalities include audio recordings, symbolic music scores, mid-level representations, motion, and gestural data, video recordings, editorial or cultural tags, lyrics and album cover arts. This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval and highlights how multimodal algorithms can help Music Computing applications. First, we categorize the related literature based on the application they address. Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus in the next years

Teasing apart retrieval and encoding interference in the processing of anaphors

Two classes of account have been proposed to explain the memory processes subserving the processing of reflexive-antecedent dependencies. Structure-based accounts assume that the retrieval of the antecedent is guided by syntactic tree-configurational information without considering other kinds of information such as gender marking in the case of English reflexives. By contrast, unconstrained cue-based retrieval assumes that all available information is used for retrieving the antecedent. Similarity-based interference effects from structurally illicit distractors which match a non-structural retrieval cue have been interpreted as evidence favoring the unconstrained cue-based retrieval account since cue-based retrieval interference from structurally illicit distractors is incompatible with the structure-based account. However, it has been argued that the observed effects do not necessarily reflect interference occurring at the moment of retrieval but might equally well be accounted for by interference occurring already at the stage of encoding or maintaining the antecedent in memory, in which case they cannot be taken as evidence against the structure-based account. We present three experiments (self-paced reading and eye-tracking) on German reflexives and Swedish reflexive and pronominal possessives in which we pit the predictions of encoding interference and cue-based retrieval interference against each other. We could not find any indication that encoding interference affects the processing ease of the reflexive-antecedent dependency formation. Thus, there is no evidence that encoding interference might be the explanation for the interference effects observed in previous work. We therefore conclude that invoking encoding interference may not be a plausible way to reconcile interference effects with a structure-based account of reflexive processing

Towards the ontology-based approach for factual information matching

Factual information is information based on facts or relating to facts. The reliability of automatically extracted facts is the main problem of processing factual information. The fact retrieval system remains one of the most effective tools for identifying the information for decision-making. In this work, we explore how can natural language processing methods and problem domain ontology help to check contradictions and mismatches in facts automatically