The study of probability model for compound similarity searching

Information Retrieval or IR system main task is to retrieve relevant documents according to the users query. One of IR most popular retrieval model is the Vector Space Model. This model assumes relevance based on similarity, which is defined as the distance between query and document in the concept space. All currently existing chemical compound database systems have adapt the vector space model to calculate the similarity of a database entry to a query compound. However, it assumes that fragments represented by the bits are independent of one another, which is not necessarily true. Hence, the possibility of applying another IR model is explored, which is the Probabilistic Model, for chemical compound searching. This model estimates the probabilities of a chemical structure to have the same bioactivity as a target compound. It is envisioned that by ranking chemical structures in decreasing order of their probability of relevance to the query structure, the effectiveness of a molecular similarity searching system can be increased. Both fragment dependencies and independencies assumption are taken into consideration in achieving improvement towards compound similarity searching system. After conducting a series of simulated similarity searching, it is concluded that PM approaches really did perform better than the existing similarity searching. It gave better result in all evaluation criteria to confirm this statement. In terms of which probability model performs better, the BD model shown improvement over the BIR model

Parsing with parallelism : a spreading-activation model of inference processing during text understanding

The past decade of reseatch in Natural Language Processing has universally recognized that, since natural language input is almost always ambiguous with respect to its pragmatic implications, its syntactic parse, and even its lexical analysis (i.e., choice of correct word-sense for an ambiguous word), processing natural language input requires decisions about word meanings, syntactic structure, and pragmatic inferences. The lexical, syntactic, and pragmatic levels of inferencing are not as disparate as they have often been treated in both psychological and artificial intelligence research. In fact, these three levels of analysis interact to form a joint interpretation of text.ATLAST (A Three-level Language Analysis SysTem) is an implemented integration of human language understanding at the lexical, the syntactic, and the pragmatic levels. For psychological validity, ATLAST is based on results of experiments with human subjects. The ATLAST model uses a new architecture which was developed to incorporate three features: spreading activation memory, two-stage syntax, and parallel processing of syntax and semantics. It is also a new framework within which to interpret and tackle unsolved problems through implementation and experimentation

New Path Based Index Structure for Processing CAS Queries over XML Database

Querying nested data has become one of the most challenging issues for retrieving desired information from the Web. Today diverse applications generate a tremendous amount of data in different formats. These data and information exchanged on the Web are commonly expressed as nested representation such as XML, JSON, etc. Unlike the traditional database system, they don\u27t have a rigid schema. In general, the nested data is managed by storing data and its structures separately which significantly reduces the performance of data retrieving. Ensuring efficiency of processing queries which locates the exact positions of the elements has become a big challenging issue. There are different indexing structures which have been proposed in the literature to improve the performance of the query processing on the nested structure. Most of the past researches on nested structure concentrate on the structure alone. This paper proposes new index structure which combines siblings of the terminal nodes as one path which efficiently processes twig queries with less number of lookups and joins. The proposed approach is compared with some of the existing approaches. The results also show that they are processed with better performance compared to the existing ones

When Alcoholism Affects Memory Functions: MRI of the Brain.

The development of modern imaging techniques makes it possible to examine directly the relationship between brain abnormalities and memory impairment. Alcoholic amnesics may perform normally on certain tests (priming tasks) that require implicit (unconscious) memory, even though they may not be able consciously to recall the memory. Researchers have therefore postulated the existence of multiple memory mechanisms. Magnetic resonance imaging (MRI) observations suggest that independent memory mechanisms are not necessary to explain the dissociation between explicit and implicit memory. Alcoholic amnesics appear to suffer from damage to structures in two areas of the brain, affecting two separate processing components that are both required in most priming tasks: a stimulus processing component and a memory processing component

Planning ahead: How recent experience with structures and words changes the scope of linguistic planning

The scope of linguistic planning, i.e., the amount of linguistic information that speakers prepare in advance for an utterance they are about to produce, is highly variable. Distinguishing between possible sources of this variability provides a way to discriminate between production accounts that assume structurally incremental and lexically incremental sentence planning. Two picture-naming experiments evaluated changes in speakers’ planning scope as a function of experience with message structure, sentence structure, and lexical items. On target trials participants produced sentences beginning with two semantically related or unrelated objects in the same complex noun phrase. To manipulate familiarity with sentence structure, target displays were preceded by prime displays that elicited the same or different sentence structures. To manipulate ease of lexical retrieval, target sentences began either with the higher-frequency or lower-frequency member of each semantic pair. The results show that repetition of sentence structure can extend speakers’ scope of planning from one to two words in a complex noun phrase, as indexed by the presence of semantic interference in structurally primed sentences beginning with easily retrievable words. Changes in planning scope tied to experience with phrasal structures favor production accounts assuming structural planning in early sentence formulation